SHOGUN  4.1.0
class_list.cpp
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1 /*
2  * This program is free software; you can redistribute it and/or modify
3  * it under the terms of the GNU General Public License as published by
4  * the Free Software Foundation; either version 3 of the License, or
5  * (at your option) any later version.
6  *
7  * Written (W) 2009 Soeren Sonnenburg
8  * Copyright (C) 2009 Fraunhofer Institute FIRST and Max-Planck-Society
9  */
10 
11 #include <shogun/lib/common.h>
12 #include <shogun/base/class_list.h>
13 #include <string.h>
14 
19 #include <shogun/structure/Plif.h>
56 #include <shogun/classifier/LDA.h>
92 #include <shogun/io/ProtobufFile.h>
93 #include <shogun/io/BinaryFile.h>
95 #include <shogun/io/LineReader.h>
96 #include <shogun/io/SimpleFile.h>
97 #include <shogun/io/LibSVMFile.h>
98 #include <shogun/io/File.h>
100 #include <shogun/io/IOBuffer.h>
101 #include <shogun/io/UAIFile.h>
102 #include <shogun/io/Parser.h>
103 #include <shogun/io/BinaryStream.h>
104 #include <shogun/io/CSVFile.h>
115 #include <shogun/lib/Cache.h>
116 #include <shogun/lib/Data.h>
118 #include <shogun/lib/Compressor.h>
120 #include <shogun/lib/BitString.h>
121 #include <shogun/lib/Hash.h>
123 #include <shogun/lib/Signal.h>
125 #include <shogun/lib/Set.h>
126 #include <shogun/lib/DynamicArray.h>
128 #include <shogun/lib/IndexBlock.h>
129 #include <shogun/lib/Time.h>
131 #include <shogun/lib/List.h>
152 #include <shogun/converter/Isomap.h>
172 #include <shogun/multiclass/QDA.h>
179 #include <shogun/multiclass/KNN.h>
180 #include <shogun/multiclass/MCLDA.h>
228 #include <shogun/machine/Machine.h>
285 #include <shogun/ui/GUIFeatures.h>
286 #include <shogun/ui/GUIMath.h>
288 #include <shogun/ui/GUIHMM.h>
289 #include <shogun/ui/GUIDistance.h>
290 #include <shogun/ui/GUITime.h>
291 #include <shogun/ui/GUIConverter.h>
292 #include <shogun/ui/GUIStructure.h>
293 #include <shogun/ui/GUIKernel.h>
295 #include <shogun/ui/GUILabels.h>
296 #include <shogun/ui/GUIClassifier.h>
309 #include <shogun/mathematics/Math.h>
348 #include <shogun/neuralnets/RBM.h>
372 #include <shogun/clustering/GMM.h>
375 #include <shogun/latent/LatentSVM.h>
376 #include <shogun/metric/LMNN.h>
386 #include <shogun/preprocessor/PCA.h>
405 #include <shogun/loss/HuberLoss.h>
406 #include <shogun/loss/SquaredLoss.h>
408 #include <shogun/loss/HingeLoss.h>
409 #include <shogun/loss/LogLoss.h>
427 #include <shogun/kernel/AUCKernel.h>
438 #include <shogun/kernel/LogKernel.h>
484 #include <shogun/statistics/HSIC.h>
489 #include <shogun/statistics/NOCCO.h>
507 #include <shogun/features/Subset.h>
533 using namespace shogun;
534 
535 #define SHOGUN_TEMPLATE_CLASS
536 #define SHOGUN_BASIC_CLASS
537 static SHOGUN_BASIC_CLASS CSGObject* __new_CSequence(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSequence(): NULL; }
538 static SHOGUN_BASIC_CLASS CSGObject* __new_CSequenceLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSequenceLabels(): NULL; }
539 static SHOGUN_BASIC_CLASS CSGObject* __new_CGraphCut(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGraphCut(): NULL; }
541 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorType(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorType(): NULL; }
542 static SHOGUN_BASIC_CLASS CSGObject* __new_CTableFactorType(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTableFactorType(): NULL; }
543 static SHOGUN_BASIC_CLASS CSGObject* __new_CPlif(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPlif(): NULL; }
544 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassModel(): NULL; }
545 static SHOGUN_BASIC_CLASS CSGObject* __new_CPlifArray(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPlifArray(): NULL; }
546 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorDataSource(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorDataSource(): NULL; }
547 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactor(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactor(): NULL; }
548 static SHOGUN_BASIC_CLASS CSGObject* __new_CTwoStateModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTwoStateModel(): NULL; }
550 static SHOGUN_BASIC_CLASS CSGObject* __new_CStochasticSOSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStochasticSOSVM(): NULL; }
551 static SHOGUN_BASIC_CLASS CSGObject* __new_CIntronList(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIntronList(): NULL; }
552 static SHOGUN_BASIC_CLASS CSGObject* __new_CFWSOSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFWSOSVM(): NULL; }
553 static SHOGUN_BASIC_CLASS CSGObject* __new_CSparseMultilabel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSparseMultilabel(): NULL; }
554 static SHOGUN_BASIC_CLASS CSGObject* __new_CMultilabelSOLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMultilabelSOLabels(): NULL; }
555 static SHOGUN_BASIC_CLASS CSGObject* __new_CDualLibQPBMSOSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDualLibQPBMSOSVM(): NULL; }
556 static SHOGUN_BASIC_CLASS CSGObject* __new_CSOSVMHelper(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSOSVMHelper(): NULL; }
557 static SHOGUN_BASIC_CLASS CSGObject* __new_CSegmentLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSegmentLoss(): NULL; }
558 static SHOGUN_BASIC_CLASS CSGObject* __new_CGEMPLP(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGEMPLP(): NULL; }
559 static SHOGUN_BASIC_CLASS CSGObject* __new_CHMSVMModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHMSVMModel(): NULL; }
560 static SHOGUN_BASIC_CLASS CSGObject* __new_CMultilabelModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMultilabelModel(): NULL; }
561 static SHOGUN_BASIC_CLASS CSGObject* __new_CDisjointSet(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDisjointSet(): NULL; }
562 static SHOGUN_BASIC_CLASS CSGObject* __new_CMAPInference(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMAPInference(): NULL; }
563 static SHOGUN_BASIC_CLASS CSGObject* __new_CPlifMatrix(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPlifMatrix(): NULL; }
564 static SHOGUN_BASIC_CLASS CSGObject* __new_CCCSOSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCCSOSVM(): NULL; }
565 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorGraph(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorGraph(): NULL; }
567 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorGraphModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorGraphModel(): NULL; }
568 static SHOGUN_BASIC_CLASS CSGObject* __new_CMultilabelCLRModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMultilabelCLRModel(): NULL; }
569 static SHOGUN_BASIC_CLASS CSGObject* __new_CDynProg(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDynProg(): NULL; }
570 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassSOLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassSOLabels(): NULL; }
571 static SHOGUN_BASIC_CLASS CSGObject* __new_CWeightedMajorityVote(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CWeightedMajorityVote(): NULL; }
572 static SHOGUN_BASIC_CLASS CSGObject* __new_CMeanRule(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMeanRule(): NULL; }
573 static SHOGUN_BASIC_CLASS CSGObject* __new_CMajorityVote(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMajorityVote(): NULL; }
576 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibLinearRegression(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibLinearRegression(): NULL; }
577 static SHOGUN_BASIC_CLASS CSGObject* __new_CMKLRegression(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMKLRegression(): NULL; }
578 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibSVR(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibSVR(): NULL; }
581 static SHOGUN_BASIC_CLASS CSGObject* __new_CLeastAngleRegression(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLeastAngleRegression(): NULL; }
582 static SHOGUN_BASIC_CLASS CSGObject* __new_COnlineLibLinear(EPrimitiveType g) { return g == PT_NOT_GENERIC? new COnlineLibLinear(): NULL; }
583 static SHOGUN_BASIC_CLASS CSGObject* __new_CSVMOcas(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSVMOcas(): NULL; }
584 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibSVMOneClass(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibSVMOneClass(): NULL; }
585 static SHOGUN_BASIC_CLASS CSGObject* __new_CSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSVM(): NULL; }
586 static SHOGUN_BASIC_CLASS CSGObject* __new_COnlineSVMSGD(EPrimitiveType g) { return g == PT_NOT_GENERIC? new COnlineSVMSGD(): NULL; }
587 static SHOGUN_BASIC_CLASS CSGObject* __new_CSVMLin(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSVMLin(): NULL; }
588 static SHOGUN_BASIC_CLASS CSGObject* __new_CSGDQN(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSGDQN(): NULL; }
589 static SHOGUN_BASIC_CLASS CSGObject* __new_CWDSVMOcas(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CWDSVMOcas(): NULL; }
590 static SHOGUN_BASIC_CLASS CSGObject* __new_CNewtonSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNewtonSVM(): NULL; }
591 static SHOGUN_BASIC_CLASS CSGObject* __new_CGNPPLib(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGNPPLib(): NULL; }
592 static SHOGUN_BASIC_CLASS CSGObject* __new_CSVMSGD(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSVMSGD(): NULL; }
593 static SHOGUN_BASIC_CLASS CSGObject* __new_CQPBSVMLib(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CQPBSVMLib(): NULL; }
594 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibLinear(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibLinear(): NULL; }
595 static SHOGUN_BASIC_CLASS CSGObject* __new_CGPBTSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGPBTSVM(): NULL; }
596 static SHOGUN_BASIC_CLASS CSGObject* __new_CGNPPSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGNPPSVM(): NULL; }
597 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibSVM(): NULL; }
598 static SHOGUN_BASIC_CLASS CSGObject* __new_CMPDSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMPDSVM(): NULL; }
599 static SHOGUN_BASIC_CLASS CSGObject* __new_CLDA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLDA(): NULL; }
600 static SHOGUN_BASIC_CLASS CSGObject* __new_CNearestCentroid(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNearestCentroid(): NULL; }
601 static SHOGUN_BASIC_CLASS CSGObject* __new_CMKLMulticlass(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMKLMulticlass(): NULL; }
602 static SHOGUN_BASIC_CLASS CSGObject* __new_CMKLOneClass(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMKLOneClass(): NULL; }
603 static SHOGUN_BASIC_CLASS CSGObject* __new_CMKLClassification(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMKLClassification(): NULL; }
604 static SHOGUN_BASIC_CLASS CSGObject* __new_CVowpalWabbit(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVowpalWabbit(): NULL; }
605 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwRegressor(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwRegressor(): NULL; }
606 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwNativeCacheWriter(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwNativeCacheWriter(): NULL; }
607 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwNativeCacheReader(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwNativeCacheReader(): NULL; }
608 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwEnvironment(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwEnvironment(): NULL; }
609 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwParser(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwParser(): NULL; }
610 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwAdaptiveLearner(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwAdaptiveLearner(): NULL; }
611 static SHOGUN_BASIC_CLASS CSGObject* __new_CVwNonAdaptiveLearner(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CVwNonAdaptiveLearner(): NULL; }
612 static SHOGUN_BASIC_CLASS CSGObject* __new_CAveragedPerceptron(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CAveragedPerceptron(): NULL; }
614 static SHOGUN_BASIC_CLASS CSGObject* __new_CPluginEstimate(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPluginEstimate(): NULL; }
615 static SHOGUN_BASIC_CLASS CSGObject* __new_CPerceptron(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPerceptron(): NULL; }
617 static SHOGUN_BASIC_CLASS CSGObject* __new_CMinimizerContext(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMinimizerContext(): NULL; }
618 static SHOGUN_BASIC_CLASS CSGObject* __new_CTron(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTron(): NULL; }
619 static SHOGUN_BASIC_CLASS CSGObject* __new_CProtobufFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CProtobufFile(): NULL; }
620 static SHOGUN_BASIC_CLASS CSGObject* __new_CStreamingFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStreamingFile(): NULL; }
621 static SHOGUN_BASIC_CLASS CSGObject* __new_CStreamingVwCacheFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStreamingVwCacheFile(): NULL; }
623 static SHOGUN_BASIC_CLASS CSGObject* __new_CStreamingVwFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStreamingVwFile(): NULL; }
624 static SHOGUN_BASIC_CLASS CSGObject* __new_CStreamingAsciiFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStreamingAsciiFile(): NULL; }
625 static SHOGUN_BASIC_CLASS CSGObject* __new_CBinaryFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBinaryFile(): NULL; }
626 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralNetworkFileReader(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralNetworkFileReader(): NULL; }
627 static SHOGUN_BASIC_CLASS CSGObject* __new_CLineReader(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLineReader(): NULL; }
628 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibSVMFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibSVMFile(): NULL; }
629 static SHOGUN_BASIC_CLASS CSGObject* __new_CFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFile(): NULL; }
631 static SHOGUN_BASIC_CLASS CSGObject* __new_CIOBuffer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIOBuffer(): NULL; }
632 static SHOGUN_BASIC_CLASS CSGObject* __new_CUAIFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CUAIFile(): NULL; }
633 static SHOGUN_BASIC_CLASS CSGObject* __new_CParser(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CParser(): NULL; }
634 static SHOGUN_BASIC_CLASS CSGObject* __new_CCSVFile(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCSVFile(): NULL; }
635 static SHOGUN_BASIC_CLASS CSGObject* __new_CData(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CData(): NULL; }
636 static SHOGUN_BASIC_CLASS CSGObject* __new_CDelimiterTokenizer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDelimiterTokenizer(): NULL; }
637 static SHOGUN_BASIC_CLASS CSGObject* __new_CCompressor(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCompressor(): NULL; }
638 static SHOGUN_BASIC_CLASS CSGObject* __new_CIndexBlockGroup(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIndexBlockGroup(): NULL; }
639 static SHOGUN_BASIC_CLASS CSGObject* __new_CBitString(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBitString(): NULL; }
640 static SHOGUN_BASIC_CLASS CSGObject* __new_CHash(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHash(): NULL; }
641 static SHOGUN_BASIC_CLASS CSGObject* __new_CJobResult(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJobResult(): NULL; }
643 static SHOGUN_BASIC_CLASS CSGObject* __new_CStructuredData(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStructuredData(): NULL; }
644 static SHOGUN_BASIC_CLASS CSGObject* __new_CSignal(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSignal(): NULL; }
645 static SHOGUN_BASIC_CLASS CSGObject* __new_CIndexBlockTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIndexBlockTree(): NULL; }
646 static SHOGUN_BASIC_CLASS CSGObject* __new_CCircularBuffer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCircularBuffer(): NULL; }
647 static SHOGUN_BASIC_CLASS CSGObject* __new_CIndexBlock(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIndexBlock(): NULL; }
648 static SHOGUN_BASIC_CLASS CSGObject* __new_CTime(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTime(): NULL; }
649 static SHOGUN_BASIC_CLASS CSGObject* __new_CNGramTokenizer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNGramTokenizer(): NULL; }
650 static SHOGUN_BASIC_CLASS CSGObject* __new_CListElement(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CListElement(): NULL; }
651 static SHOGUN_BASIC_CLASS CSGObject* __new_CList(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CList(): NULL; }
652 static SHOGUN_BASIC_CLASS CSGObject* __new_CDynamicObjectArray(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDynamicObjectArray(): NULL; }
653 static SHOGUN_BASIC_CLASS CSGObject* __new_CDiffusionMaps(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDiffusionMaps(): NULL; }
656 static SHOGUN_BASIC_CLASS CSGObject* __new_CSOBI(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSOBI(): NULL; }
657 static SHOGUN_BASIC_CLASS CSGObject* __new_CJediSep(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJediSep(): NULL; }
658 static SHOGUN_BASIC_CLASS CSGObject* __new_CUWedgeSep(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CUWedgeSep(): NULL; }
659 static SHOGUN_BASIC_CLASS CSGObject* __new_CJade(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJade(): NULL; }
660 static SHOGUN_BASIC_CLASS CSGObject* __new_CFFSep(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFFSep(): NULL; }
661 static SHOGUN_BASIC_CLASS CSGObject* __new_CFastICA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFastICA(): NULL; }
663 static SHOGUN_BASIC_CLASS CSGObject* __new_CLaplacianEigenmaps(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLaplacianEigenmaps(): NULL; }
664 static SHOGUN_BASIC_CLASS CSGObject* __new_CHashedDocConverter(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHashedDocConverter(): NULL; }
666 static SHOGUN_BASIC_CLASS CSGObject* __new_CManifoldSculpting(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CManifoldSculpting(): NULL; }
668 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorAnalysis(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorAnalysis(): NULL; }
673 static SHOGUN_BASIC_CLASS CSGObject* __new_CIsomap(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIsomap(): NULL; }
677 static SHOGUN_BASIC_CLASS CSGObject* __new_CParameterCombination(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CParameterCombination(): NULL; }
680 static SHOGUN_BASIC_CLASS CSGObject* __new_CGMNPLib(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGMNPLib(): NULL; }
682 static SHOGUN_BASIC_CLASS CSGObject* __new_CLaRank(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLaRank(): NULL; }
683 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCForestEncoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCForestEncoder(): NULL; }
685 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCAEDDecoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCAEDDecoder(): NULL; }
687 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCEDDecoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCEDDecoder(): NULL; }
688 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCOVREncoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCOVREncoder(): NULL; }
689 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCIHDDecoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCIHDDecoder(): NULL; }
690 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCHDDecoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCHDDecoder(): NULL; }
692 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCLLBDecoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCLLBDecoder(): NULL; }
693 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCOVOEncoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCOVOEncoder(): NULL; }
694 static SHOGUN_BASIC_CLASS CSGObject* __new_CECOCStrategy(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CECOCStrategy(): NULL; }
695 static SHOGUN_BASIC_CLASS CSGObject* __new_CShareBoost(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CShareBoost(): NULL; }
698 static SHOGUN_BASIC_CLASS CSGObject* __new_CGMNPSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGMNPSVM(): NULL; }
699 static SHOGUN_BASIC_CLASS CSGObject* __new_CQDA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CQDA(): NULL; }
700 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassSVM(): NULL; }
701 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassOCAS(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassOCAS(): NULL; }
702 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassLibLinear(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassLibLinear(): NULL; }
703 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassLibSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassLibSVM(): NULL; }
704 static SHOGUN_BASIC_CLASS CSGObject* __new_CID3ClassifierTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CID3ClassifierTree(): NULL; }
705 static SHOGUN_BASIC_CLASS CSGObject* __new_CRelaxedTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRelaxedTree(): NULL; }
707 static SHOGUN_BASIC_CLASS CSGObject* __new_CCARTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCARTree(): NULL; }
708 static SHOGUN_BASIC_CLASS CSGObject* __new_CCHAIDTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCHAIDTree(): NULL; }
710 static SHOGUN_BASIC_CLASS CSGObject* __new_CC45ClassifierTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CC45ClassifierTree(): NULL; }
711 static SHOGUN_BASIC_CLASS CSGObject* __new_CKDTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKDTree(): NULL; }
712 static SHOGUN_BASIC_CLASS CSGObject* __new_CRandomCARTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRandomCARTree(): NULL; }
713 static SHOGUN_BASIC_CLASS CSGObject* __new_CBallTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBallTree(): NULL; }
717 static SHOGUN_BASIC_CLASS CSGObject* __new_CScatterSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CScatterSVM(): NULL; }
718 static SHOGUN_BASIC_CLASS CSGObject* __new_CKNN(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKNN(): NULL; }
719 static SHOGUN_BASIC_CLASS CSGObject* __new_CMCLDA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMCLDA(): NULL; }
720 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussianNaiveBayes(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussianNaiveBayes(): NULL; }
722 static SHOGUN_BASIC_CLASS CSGObject* __new_CChebyshewMetric(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CChebyshewMetric(): NULL; }
723 static SHOGUN_BASIC_CLASS CSGObject* __new_CJensenMetric(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJensenMetric(): NULL; }
724 static SHOGUN_BASIC_CLASS CSGObject* __new_CChiSquareDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CChiSquareDistance(): NULL; }
725 static SHOGUN_BASIC_CLASS CSGObject* __new_CManhattanMetric(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CManhattanMetric(): NULL; }
727 static SHOGUN_BASIC_CLASS CSGObject* __new_CTanimotoDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTanimotoDistance(): NULL; }
728 static SHOGUN_BASIC_CLASS CSGObject* __new_CKernelDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKernelDistance(): NULL; }
729 static SHOGUN_BASIC_CLASS CSGObject* __new_CCustomDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCustomDistance(): NULL; }
730 static SHOGUN_BASIC_CLASS CSGObject* __new_CBrayCurtisDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBrayCurtisDistance(): NULL; }
731 static SHOGUN_BASIC_CLASS CSGObject* __new_CCanberraWordDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCanberraWordDistance(): NULL; }
733 static SHOGUN_BASIC_CLASS CSGObject* __new_CHammingWordDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHammingWordDistance(): NULL; }
734 static SHOGUN_BASIC_CLASS CSGObject* __new_CCosineDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCosineDistance(): NULL; }
735 static SHOGUN_BASIC_CLASS CSGObject* __new_CMahalanobisDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMahalanobisDistance(): NULL; }
736 static SHOGUN_BASIC_CLASS CSGObject* __new_CMinkowskiMetric(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMinkowskiMetric(): NULL; }
738 static SHOGUN_BASIC_CLASS CSGObject* __new_CEuclideanDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CEuclideanDistance(): NULL; }
739 static SHOGUN_BASIC_CLASS CSGObject* __new_CGeodesicMetric(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGeodesicMetric(): NULL; }
740 static SHOGUN_BASIC_CLASS CSGObject* __new_CCanberraMetric(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCanberraMetric(): NULL; }
742 static SHOGUN_BASIC_CLASS CSGObject* __new_CRandomForest(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRandomForest(): NULL; }
744 static SHOGUN_BASIC_CLASS CSGObject* __new_CMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMachine(): NULL; }
745 static SHOGUN_BASIC_CLASS CSGObject* __new_CDistanceMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDistanceMachine(): NULL; }
747 static SHOGUN_BASIC_CLASS CSGObject* __new_COnlineLinearMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new COnlineLinearMachine(): NULL; }
750 static SHOGUN_BASIC_CLASS CSGObject* __new_CSoftMaxLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSoftMaxLikelihood(): NULL; }
752 static SHOGUN_BASIC_CLASS CSGObject* __new_CStudentsTLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStudentsTLikelihood(): NULL; }
753 static SHOGUN_BASIC_CLASS CSGObject* __new_CProbitVGLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CProbitVGLikelihood(): NULL; }
754 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussianLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussianLikelihood(): NULL; }
764 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogitVGLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogitVGLikelihood(): NULL; }
765 static SHOGUN_BASIC_CLASS CSGObject* __new_CEPInferenceMethod(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CEPInferenceMethod(): NULL; }
767 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogitLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogitLikelihood(): NULL; }
768 static SHOGUN_BASIC_CLASS CSGObject* __new_CZeroMean(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CZeroMean(): NULL; }
769 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogitDVGLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogitDVGLikelihood(): NULL; }
771 static SHOGUN_BASIC_CLASS CSGObject* __new_CExactInferenceMethod(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CExactInferenceMethod(): NULL; }
772 static SHOGUN_BASIC_CLASS CSGObject* __new_CProbitLikelihood(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CProbitLikelihood(): NULL; }
774 static SHOGUN_BASIC_CLASS CSGObject* __new_CConstMean(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CConstMean(): NULL; }
775 static SHOGUN_BASIC_CLASS CSGObject* __new_CFITCInferenceMethod(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFITCInferenceMethod(): NULL; }
777 static SHOGUN_BASIC_CLASS CSGObject* __new_CLinearMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLinearMachine(): NULL; }
780 static SHOGUN_BASIC_CLASS CSGObject* __new_CKernelMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKernelMachine(): NULL; }
781 static SHOGUN_BASIC_CLASS CSGObject* __new_CBaggingMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBaggingMachine(): NULL; }
782 static SHOGUN_BASIC_CLASS CSGObject* __new_CStochasticGBMachine(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStochasticGBMachine(): NULL; }
784 static SHOGUN_BASIC_CLASS CSGObject* __new_CLibLinearMTL(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLibLinearMTL(): NULL; }
786 static SHOGUN_BASIC_CLASS CSGObject* __new_CTask(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTask(): NULL; }
787 static SHOGUN_BASIC_CLASS CSGObject* __new_CNode(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNode(): NULL; }
788 static SHOGUN_BASIC_CLASS CSGObject* __new_CTaxonomy(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTaxonomy(): NULL; }
792 static SHOGUN_BASIC_CLASS CSGObject* __new_CTaskTree(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTaskTree(): NULL; }
796 static SHOGUN_BASIC_CLASS CSGObject* __new_CTaskGroup(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTaskGroup(): NULL; }
803 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIFeatures(): NULL; }
804 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIMath(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIMath(): NULL; }
805 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIPreprocessor(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIPreprocessor(): NULL; }
806 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIHMM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIHMM(): NULL; }
807 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIDistance(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIDistance(): NULL; }
808 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUITime(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUITime(): NULL; }
809 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIConverter(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIConverter(): NULL; }
810 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIStructure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIStructure(): NULL; }
811 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIKernel(): NULL; }
812 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIPluginEstimate(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIPluginEstimate(): NULL; }
813 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUILabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUILabels(): NULL; }
814 static SHOGUN_BASIC_CLASS CSGObject* __new_CGUIClassifier(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGUIClassifier(): NULL; }
815 static SHOGUN_BASIC_CLASS CSGObject* __new_CHMM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHMM(): NULL; }
816 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussian(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussian(): NULL; }
817 static SHOGUN_BASIC_CLASS CSGObject* __new_CHistogram(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHistogram(): NULL; }
818 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussianDistribution(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussianDistribution(): NULL; }
819 static SHOGUN_BASIC_CLASS CSGObject* __new_CPositionalPWM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPositionalPWM(): NULL; }
820 static SHOGUN_BASIC_CLASS CSGObject* __new_CMixtureModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMixtureModel(): NULL; }
821 static SHOGUN_BASIC_CLASS CSGObject* __new_CKernelDensity(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKernelDensity(): NULL; }
822 static SHOGUN_BASIC_CLASS CSGObject* __new_CLinearHMM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLinearHMM(): NULL; }
823 static SHOGUN_BASIC_CLASS CSGObject* __new_CEMMixtureModel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CEMMixtureModel(): NULL; }
825 static SHOGUN_BASIC_CLASS CSGObject* __new_CQDiag(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CQDiag(): NULL; }
826 static SHOGUN_BASIC_CLASS CSGObject* __new_CUWedge(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CUWedge(): NULL; }
827 static SHOGUN_BASIC_CLASS CSGObject* __new_CJediDiag(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJediDiag(): NULL; }
828 static SHOGUN_BASIC_CLASS CSGObject* __new_CJADiag(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJADiag(): NULL; }
829 static SHOGUN_BASIC_CLASS CSGObject* __new_CFFDiag(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFFDiag(): NULL; }
830 static SHOGUN_BASIC_CLASS CSGObject* __new_CJADiagOrth(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJADiagOrth(): NULL; }
831 static SHOGUN_BASIC_CLASS CSGObject* __new_CStatistics(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStatistics(): NULL; }
832 static SHOGUN_BASIC_CLASS CSGObject* __new_CRandom(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRandom(): NULL; }
833 static SHOGUN_BASIC_CLASS CSGObject* __new_CMath(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMath(): NULL; }
835 static SHOGUN_BASIC_CLASS CSGObject* __new_CIntegration(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIntegration(): NULL; }
839 static SHOGUN_BASIC_CLASS CSGObject* __new_CNormalSampler(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNormalSampler(): NULL; }
840 static SHOGUN_BASIC_CLASS CSGObject* __new_CProbingSampler(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CProbingSampler(): NULL; }
841 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogDetEstimator(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogDetEstimator(): NULL; }
842 static SHOGUN_BASIC_CLASS CSGObject* __new_CDenseExactLogJob(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDenseExactLogJob(): NULL; }
846 static SHOGUN_BASIC_CLASS CSGObject* __new_CDenseMatrixExactLog(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDenseMatrixExactLog(): NULL; }
849 static SHOGUN_BASIC_CLASS CSGObject* __new_CLanczosEigenSolver(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLanczosEigenSolver(): NULL; }
850 static SHOGUN_BASIC_CLASS CSGObject* __new_CDirectEigenSolver(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDirectEigenSolver(): NULL; }
851 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralSoftmaxLayer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralSoftmaxLayer(): NULL; }
852 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralLinearLayer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralLinearLayer(): NULL; }
854 static SHOGUN_BASIC_CLASS CSGObject* __new_CDeepAutoencoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDeepAutoencoder(): NULL; }
855 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralNetwork(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralNetwork(): NULL; }
857 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralLayers(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralLayers(): NULL; }
858 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralLayer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralLayer(): NULL; }
859 static SHOGUN_BASIC_CLASS CSGObject* __new_CDeepBeliefNetwork(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDeepBeliefNetwork(): NULL; }
860 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralInputLayer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralInputLayer(): NULL; }
861 static SHOGUN_BASIC_CLASS CSGObject* __new_CNeuralLogisticLayer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNeuralLogisticLayer(): NULL; }
862 static SHOGUN_BASIC_CLASS CSGObject* __new_CAutoencoder(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CAutoencoder(): NULL; }
864 static SHOGUN_BASIC_CLASS CSGObject* __new_CRBM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRBM(): NULL; }
865 static SHOGUN_BASIC_CLASS CSGObject* __new_CROCEvaluation(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CROCEvaluation(): NULL; }
866 static SHOGUN_BASIC_CLASS CSGObject* __new_CGradientCriterion(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGradientCriterion(): NULL; }
867 static SHOGUN_BASIC_CLASS CSGObject* __new_CMultilabelAccuracy(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMultilabelAccuracy(): NULL; }
868 static SHOGUN_BASIC_CLASS CSGObject* __new_CGradientResult(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGradientResult(): NULL; }
869 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassAccuracy(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassAccuracy(): NULL; }
872 static SHOGUN_BASIC_CLASS CSGObject* __new_CMeanSquaredError(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMeanSquaredError(): NULL; }
873 static SHOGUN_BASIC_CLASS CSGObject* __new_CGradientEvaluation(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGradientEvaluation(): NULL; }
874 static SHOGUN_BASIC_CLASS CSGObject* __new_CMeanAbsoluteError(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMeanAbsoluteError(): NULL; }
877 static SHOGUN_BASIC_CLASS CSGObject* __new_CMeanSquaredLogError(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMeanSquaredLogError(): NULL; }
879 static SHOGUN_BASIC_CLASS CSGObject* __new_CCrossValidation(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCrossValidation(): NULL; }
880 static SHOGUN_BASIC_CLASS CSGObject* __new_CClusteringAccuracy(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CClusteringAccuracy(): NULL; }
882 static SHOGUN_BASIC_CLASS CSGObject* __new_CPRCEvaluation(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPRCEvaluation(): NULL; }
883 static SHOGUN_BASIC_CLASS CSGObject* __new_CStructuredAccuracy(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStructuredAccuracy(): NULL; }
886 static SHOGUN_BASIC_CLASS CSGObject* __new_CAccuracyMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CAccuracyMeasure(): NULL; }
887 static SHOGUN_BASIC_CLASS CSGObject* __new_CErrorRateMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CErrorRateMeasure(): NULL; }
888 static SHOGUN_BASIC_CLASS CSGObject* __new_CBALMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBALMeasure(): NULL; }
889 static SHOGUN_BASIC_CLASS CSGObject* __new_CWRACCMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CWRACCMeasure(): NULL; }
890 static SHOGUN_BASIC_CLASS CSGObject* __new_CF1Measure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CF1Measure(): NULL; }
892 static SHOGUN_BASIC_CLASS CSGObject* __new_CRecallMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRecallMeasure(): NULL; }
893 static SHOGUN_BASIC_CLASS CSGObject* __new_CPrecisionMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPrecisionMeasure(): NULL; }
894 static SHOGUN_BASIC_CLASS CSGObject* __new_CSpecificityMeasure(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSpecificityMeasure(): NULL; }
897 static SHOGUN_BASIC_CLASS CSGObject* __new_CHierarchical(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHierarchical(): NULL; }
898 static SHOGUN_BASIC_CLASS CSGObject* __new_CGMM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGMM(): NULL; }
899 static SHOGUN_BASIC_CLASS CSGObject* __new_CKMeans(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKMeans(): NULL; }
900 static SHOGUN_BASIC_CLASS CSGObject* __new_CLatentSOSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLatentSOSVM(): NULL; }
901 static SHOGUN_BASIC_CLASS CSGObject* __new_CLatentSVM(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLatentSVM(): NULL; }
902 static SHOGUN_BASIC_CLASS CSGObject* __new_CLMNN(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLMNN(): NULL; }
903 static SHOGUN_BASIC_CLASS CSGObject* __new_CLMNNStatistics(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLMNNStatistics(): NULL; }
905 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorGraphLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorGraphLabels(): NULL; }
906 static SHOGUN_BASIC_CLASS CSGObject* __new_CLabelsFactory(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLabelsFactory(): NULL; }
907 static SHOGUN_BASIC_CLASS CSGObject* __new_CRegressionLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRegressionLabels(): NULL; }
908 static SHOGUN_BASIC_CLASS CSGObject* __new_CMultilabelLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMultilabelLabels(): NULL; }
909 static SHOGUN_BASIC_CLASS CSGObject* __new_CLatentLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLatentLabels(): NULL; }
910 static SHOGUN_BASIC_CLASS CSGObject* __new_CStructuredLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStructuredLabels(): NULL; }
911 static SHOGUN_BASIC_CLASS CSGObject* __new_CBinaryLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBinaryLabels(): NULL; }
912 static SHOGUN_BASIC_CLASS CSGObject* __new_CMulticlassLabels(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMulticlassLabels(): NULL; }
913 static SHOGUN_BASIC_CLASS CSGObject* __new_CPCA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPCA(): NULL; }
914 static SHOGUN_BASIC_CLASS CSGObject* __new_CFisherLDA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFisherLDA(): NULL; }
915 static SHOGUN_BASIC_CLASS CSGObject* __new_CPNorm(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPNorm(): NULL; }
916 static SHOGUN_BASIC_CLASS CSGObject* __new_CHomogeneousKernelMap(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHomogeneousKernelMap(): NULL; }
917 static SHOGUN_BASIC_CLASS CSGObject* __new_CSortWordString(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSortWordString(): NULL; }
918 static SHOGUN_BASIC_CLASS CSGObject* __new_CSortUlongString(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSortUlongString(): NULL; }
919 static SHOGUN_BASIC_CLASS CSGObject* __new_CPruneVarSubMean(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPruneVarSubMean(): NULL; }
920 static SHOGUN_BASIC_CLASS CSGObject* __new_CRescaleFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRescaleFeatures(): NULL; }
921 static SHOGUN_BASIC_CLASS CSGObject* __new_CSumOne(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSumOne(): NULL; }
922 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogPlusOne(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogPlusOne(): NULL; }
923 static SHOGUN_BASIC_CLASS CSGObject* __new_CBAHSIC(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBAHSIC(): NULL; }
924 static SHOGUN_BASIC_CLASS CSGObject* __new_CNormOne(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNormOne(): NULL; }
926 static SHOGUN_BASIC_CLASS CSGObject* __new_CKernelPCA(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKernelPCA(): NULL; }
928 static SHOGUN_BASIC_CLASS CSGObject* __new_CExponentialLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CExponentialLoss(): NULL; }
929 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogLossMargin(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogLossMargin(): NULL; }
930 static SHOGUN_BASIC_CLASS CSGObject* __new_CSquaredHingeLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSquaredHingeLoss(): NULL; }
931 static SHOGUN_BASIC_CLASS CSGObject* __new_CSmoothHingeLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSmoothHingeLoss(): NULL; }
932 static SHOGUN_BASIC_CLASS CSGObject* __new_CHuberLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHuberLoss(): NULL; }
933 static SHOGUN_BASIC_CLASS CSGObject* __new_CSquaredLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSquaredLoss(): NULL; }
935 static SHOGUN_BASIC_CLASS CSGObject* __new_CHingeLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHingeLoss(): NULL; }
936 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogLoss(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogLoss(): NULL; }
937 static SHOGUN_BASIC_CLASS CSGObject* __new_CSigmoidKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSigmoidKernel(): NULL; }
938 static SHOGUN_BASIC_CLASS CSGObject* __new_CCircularKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCircularKernel(): NULL; }
940 static SHOGUN_BASIC_CLASS CSGObject* __new_CSphericalKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSphericalKernel(): NULL; }
941 static SHOGUN_BASIC_CLASS CSGObject* __new_CMultiquadricKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CMultiquadricKernel(): NULL; }
942 static SHOGUN_BASIC_CLASS CSGObject* __new_CPolyKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPolyKernel(): NULL; }
943 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussianARDKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussianARDKernel(): NULL; }
945 static SHOGUN_BASIC_CLASS CSGObject* __new_CJensenShannonKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CJensenShannonKernel(): NULL; }
951 static SHOGUN_BASIC_CLASS CSGObject* __new_CDiceKernelNormalizer(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDiceKernelNormalizer(): NULL; }
957 static SHOGUN_BASIC_CLASS CSGObject* __new_CWaveKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CWaveKernel(): NULL; }
958 static SHOGUN_BASIC_CLASS CSGObject* __new_CConstKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CConstKernel(): NULL; }
962 static SHOGUN_BASIC_CLASS CSGObject* __new_CLinearStringKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLinearStringKernel(): NULL; }
963 static SHOGUN_BASIC_CLASS CSGObject* __new_CSpectrumRBFKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSpectrumRBFKernel(): NULL; }
968 static SHOGUN_BASIC_CLASS CSGObject* __new_CSNPStringKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSNPStringKernel(): NULL; }
969 static SHOGUN_BASIC_CLASS CSGObject* __new_CCommWordStringKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCommWordStringKernel(): NULL; }
975 static SHOGUN_BASIC_CLASS CSGObject* __new_COligoStringKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new COligoStringKernel(): NULL; }
983 static SHOGUN_BASIC_CLASS CSGObject* __new_CLinearKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLinearKernel(): NULL; }
984 static SHOGUN_BASIC_CLASS CSGObject* __new_CDistanceKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDistanceKernel(): NULL; }
985 static SHOGUN_BASIC_CLASS CSGObject* __new_CSplineKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSplineKernel(): NULL; }
986 static SHOGUN_BASIC_CLASS CSGObject* __new_CPeriodicKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPeriodicKernel(): NULL; }
987 static SHOGUN_BASIC_CLASS CSGObject* __new_CANOVAKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CANOVAKernel(): NULL; }
988 static SHOGUN_BASIC_CLASS CSGObject* __new_CAUCKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CAUCKernel(): NULL; }
989 static SHOGUN_BASIC_CLASS CSGObject* __new_CTStudentKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTStudentKernel(): NULL; }
990 static SHOGUN_BASIC_CLASS CSGObject* __new_CPyramidChi2(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPyramidChi2(): NULL; }
991 static SHOGUN_BASIC_CLASS CSGObject* __new_CCauchyKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCauchyKernel(): NULL; }
992 static SHOGUN_BASIC_CLASS CSGObject* __new_CChi2Kernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CChi2Kernel(): NULL; }
993 static SHOGUN_BASIC_CLASS CSGObject* __new_CDiagKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDiagKernel(): NULL; }
994 static SHOGUN_BASIC_CLASS CSGObject* __new_CWaveletKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CWaveletKernel(): NULL; }
995 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussianShiftKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussianShiftKernel(): NULL; }
996 static SHOGUN_BASIC_CLASS CSGObject* __new_CProductKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CProductKernel(): NULL; }
998 static SHOGUN_BASIC_CLASS CSGObject* __new_CGaussianKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CGaussianKernel(): NULL; }
999 static SHOGUN_BASIC_CLASS CSGObject* __new_CLogKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLogKernel(): NULL; }
1000 static SHOGUN_BASIC_CLASS CSGObject* __new_CCustomKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCustomKernel(): NULL; }
1002 static SHOGUN_BASIC_CLASS CSGObject* __new_CCombinedKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCombinedKernel(): NULL; }
1003 static SHOGUN_BASIC_CLASS CSGObject* __new_CPowerKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPowerKernel(): NULL; }
1004 static SHOGUN_BASIC_CLASS CSGObject* __new_CBesselKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBesselKernel(): NULL; }
1005 static SHOGUN_BASIC_CLASS CSGObject* __new_CExponentialKernel(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CExponentialKernel(): NULL; }
1010 static SHOGUN_BASIC_CLASS CSGObject* __new_CKernelMeanMatching(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CKernelMeanMatching(): NULL; }
1011 static SHOGUN_BASIC_CLASS CSGObject* __new_CHSIC(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHSIC(): NULL; }
1014 static SHOGUN_BASIC_CLASS CSGObject* __new_CQuadraticTimeMMD(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CQuadraticTimeMMD(): NULL; }
1015 static SHOGUN_BASIC_CLASS CSGObject* __new_CLinearTimeMMD(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLinearTimeMMD(): NULL; }
1016 static SHOGUN_BASIC_CLASS CSGObject* __new_CNOCCO(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CNOCCO(): NULL; }
1020 static SHOGUN_BASIC_CLASS CSGObject* __new_CStreamingVwFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CStreamingVwFeatures(): NULL; }
1021 static SHOGUN_BASIC_CLASS CSGObject* __new_CPolyFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CPolyFeatures(): NULL; }
1022 static SHOGUN_BASIC_CLASS CSGObject* __new_CRealFileFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CRealFileFeatures(): NULL; }
1023 static SHOGUN_BASIC_CLASS CSGObject* __new_CLBPPyrDotFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLBPPyrDotFeatures(): NULL; }
1024 static SHOGUN_BASIC_CLASS CSGObject* __new_CCombinedDotFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCombinedDotFeatures(): NULL; }
1025 static SHOGUN_BASIC_CLASS CSGObject* __new_CWDFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CWDFeatures(): NULL; }
1026 static SHOGUN_BASIC_CLASS CSGObject* __new_CDataGenerator(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDataGenerator(): NULL; }
1027 static SHOGUN_BASIC_CLASS CSGObject* __new_CDummyFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CDummyFeatures(): NULL; }
1028 static SHOGUN_BASIC_CLASS CSGObject* __new_CSparsePolyFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSparsePolyFeatures(): NULL; }
1029 static SHOGUN_BASIC_CLASS CSGObject* __new_CFKFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFKFeatures(): NULL; }
1030 static SHOGUN_BASIC_CLASS CSGObject* __new_CTOPFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CTOPFeatures(): NULL; }
1031 static SHOGUN_BASIC_CLASS CSGObject* __new_CHashedWDFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CHashedWDFeatures(): NULL; }
1036 static SHOGUN_BASIC_CLASS CSGObject* __new_CSubset(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSubset(): NULL; }
1037 static SHOGUN_BASIC_CLASS CSGObject* __new_CLatentFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CLatentFeatures(): NULL; }
1038 static SHOGUN_BASIC_CLASS CSGObject* __new_CBinnedDotFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CBinnedDotFeatures(): NULL; }
1040 static SHOGUN_BASIC_CLASS CSGObject* __new_CAlphabet(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CAlphabet(): NULL; }
1041 static SHOGUN_BASIC_CLASS CSGObject* __new_CSNPFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSNPFeatures(): NULL; }
1042 static SHOGUN_BASIC_CLASS CSGObject* __new_CCombinedFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CCombinedFeatures(): NULL; }
1043 static SHOGUN_BASIC_CLASS CSGObject* __new_CIndexFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CIndexFeatures(): NULL; }
1044 static SHOGUN_BASIC_CLASS CSGObject* __new_CFactorGraphFeatures(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CFactorGraphFeatures(): NULL; }
1045 static SHOGUN_BASIC_CLASS CSGObject* __new_CSubsetStack(EPrimitiveType g) { return g == PT_NOT_GENERIC? new CSubsetStack(): NULL; }
1047 {
1048  switch (g)
1049  {
1050  case PT_BOOL: return new CStreamingFileFromStringFeatures<bool>();
1051  case PT_CHAR: return new CStreamingFileFromStringFeatures<char>();
1052  case PT_INT8: return new CStreamingFileFromStringFeatures<int8_t>();
1053  case PT_UINT8: return new CStreamingFileFromStringFeatures<uint8_t>();
1054  case PT_INT16: return new CStreamingFileFromStringFeatures<int16_t>();
1055  case PT_UINT16: return new CStreamingFileFromStringFeatures<uint16_t>();
1056  case PT_INT32: return new CStreamingFileFromStringFeatures<int32_t>();
1057  case PT_UINT32: return new CStreamingFileFromStringFeatures<uint32_t>();
1058  case PT_INT64: return new CStreamingFileFromStringFeatures<int64_t>();
1059  case PT_UINT64: return new CStreamingFileFromStringFeatures<uint64_t>();
1060  case PT_FLOAT32: return new CStreamingFileFromStringFeatures<float32_t>();
1061  case PT_FLOAT64: return new CStreamingFileFromStringFeatures<float64_t>();
1062  case PT_FLOATMAX: return new CStreamingFileFromStringFeatures<floatmax_t>();
1063  case PT_COMPLEX128: return NULL;
1064  case PT_SGOBJECT:
1065  case PT_UNDEFINED: return NULL;
1066  }
1067  return NULL;
1068 }
1070 {
1071  switch (g)
1072  {
1073  case PT_BOOL: return new CStreamingFileFromDenseFeatures<bool>();
1074  case PT_CHAR: return new CStreamingFileFromDenseFeatures<char>();
1075  case PT_INT8: return new CStreamingFileFromDenseFeatures<int8_t>();
1076  case PT_UINT8: return new CStreamingFileFromDenseFeatures<uint8_t>();
1077  case PT_INT16: return new CStreamingFileFromDenseFeatures<int16_t>();
1078  case PT_UINT16: return new CStreamingFileFromDenseFeatures<uint16_t>();
1079  case PT_INT32: return new CStreamingFileFromDenseFeatures<int32_t>();
1080  case PT_UINT32: return new CStreamingFileFromDenseFeatures<uint32_t>();
1081  case PT_INT64: return new CStreamingFileFromDenseFeatures<int64_t>();
1082  case PT_UINT64: return new CStreamingFileFromDenseFeatures<uint64_t>();
1083  case PT_FLOAT32: return new CStreamingFileFromDenseFeatures<float32_t>();
1084  case PT_FLOAT64: return new CStreamingFileFromDenseFeatures<float64_t>();
1085  case PT_FLOATMAX: return new CStreamingFileFromDenseFeatures<floatmax_t>();
1086  case PT_COMPLEX128: return NULL;
1087  case PT_SGOBJECT:
1088  case PT_UNDEFINED: return NULL;
1089  }
1090  return NULL;
1091 }
1093 {
1094  switch (g)
1095  {
1096  case PT_BOOL: return new CParseBuffer<bool>();
1097  case PT_CHAR: return new CParseBuffer<char>();
1098  case PT_INT8: return new CParseBuffer<int8_t>();
1099  case PT_UINT8: return new CParseBuffer<uint8_t>();
1100  case PT_INT16: return new CParseBuffer<int16_t>();
1101  case PT_UINT16: return new CParseBuffer<uint16_t>();
1102  case PT_INT32: return new CParseBuffer<int32_t>();
1103  case PT_UINT32: return new CParseBuffer<uint32_t>();
1104  case PT_INT64: return new CParseBuffer<int64_t>();
1105  case PT_UINT64: return new CParseBuffer<uint64_t>();
1106  case PT_FLOAT32: return new CParseBuffer<float32_t>();
1107  case PT_FLOAT64: return new CParseBuffer<float64_t>();
1108  case PT_FLOATMAX: return new CParseBuffer<floatmax_t>();
1109  case PT_COMPLEX128: return NULL;
1110  case PT_SGOBJECT:
1111  case PT_UNDEFINED: return NULL;
1112  }
1113  return NULL;
1114 }
1116 {
1117  switch (g)
1118  {
1119  case PT_BOOL: return new CStreamingFileFromSparseFeatures<bool>();
1120  case PT_CHAR: return new CStreamingFileFromSparseFeatures<char>();
1121  case PT_INT8: return new CStreamingFileFromSparseFeatures<int8_t>();
1122  case PT_UINT8: return new CStreamingFileFromSparseFeatures<uint8_t>();
1123  case PT_INT16: return new CStreamingFileFromSparseFeatures<int16_t>();
1124  case PT_UINT16: return new CStreamingFileFromSparseFeatures<uint16_t>();
1125  case PT_INT32: return new CStreamingFileFromSparseFeatures<int32_t>();
1126  case PT_UINT32: return new CStreamingFileFromSparseFeatures<uint32_t>();
1127  case PT_INT64: return new CStreamingFileFromSparseFeatures<int64_t>();
1128  case PT_UINT64: return new CStreamingFileFromSparseFeatures<uint64_t>();
1129  case PT_FLOAT32: return new CStreamingFileFromSparseFeatures<float32_t>();
1130  case PT_FLOAT64: return new CStreamingFileFromSparseFeatures<float64_t>();
1131  case PT_FLOATMAX: return new CStreamingFileFromSparseFeatures<floatmax_t>();
1132  case PT_COMPLEX128: return NULL;
1133  case PT_SGOBJECT:
1134  case PT_UNDEFINED: return NULL;
1135  }
1136  return NULL;
1137 }
1139 {
1140  switch (g)
1141  {
1142  case PT_BOOL: return new CSimpleFile<bool>();
1143  case PT_CHAR: return new CSimpleFile<char>();
1144  case PT_INT8: return new CSimpleFile<int8_t>();
1145  case PT_UINT8: return new CSimpleFile<uint8_t>();
1146  case PT_INT16: return new CSimpleFile<int16_t>();
1147  case PT_UINT16: return new CSimpleFile<uint16_t>();
1148  case PT_INT32: return new CSimpleFile<int32_t>();
1149  case PT_UINT32: return new CSimpleFile<uint32_t>();
1150  case PT_INT64: return new CSimpleFile<int64_t>();
1151  case PT_UINT64: return new CSimpleFile<uint64_t>();
1152  case PT_FLOAT32: return new CSimpleFile<float32_t>();
1153  case PT_FLOAT64: return new CSimpleFile<float64_t>();
1154  case PT_FLOATMAX: return new CSimpleFile<floatmax_t>();
1155  case PT_COMPLEX128: return NULL;
1156  case PT_SGOBJECT:
1157  case PT_UNDEFINED: return NULL;
1158  }
1159  return NULL;
1160 }
1162 {
1163  switch (g)
1164  {
1165  case PT_BOOL: return new CBinaryStream<bool>();
1166  case PT_CHAR: return new CBinaryStream<char>();
1167  case PT_INT8: return new CBinaryStream<int8_t>();
1168  case PT_UINT8: return new CBinaryStream<uint8_t>();
1169  case PT_INT16: return new CBinaryStream<int16_t>();
1170  case PT_UINT16: return new CBinaryStream<uint16_t>();
1171  case PT_INT32: return new CBinaryStream<int32_t>();
1172  case PT_UINT32: return new CBinaryStream<uint32_t>();
1173  case PT_INT64: return new CBinaryStream<int64_t>();
1174  case PT_UINT64: return new CBinaryStream<uint64_t>();
1175  case PT_FLOAT32: return new CBinaryStream<float32_t>();
1176  case PT_FLOAT64: return new CBinaryStream<float64_t>();
1177  case PT_FLOATMAX: return new CBinaryStream<floatmax_t>();
1178  case PT_COMPLEX128: return NULL;
1179  case PT_SGOBJECT:
1180  case PT_UNDEFINED: return NULL;
1181  }
1182  return NULL;
1183 }
1185 {
1186  switch (g)
1187  {
1188  case PT_BOOL: return new CMemoryMappedFile<bool>();
1189  case PT_CHAR: return new CMemoryMappedFile<char>();
1190  case PT_INT8: return new CMemoryMappedFile<int8_t>();
1191  case PT_UINT8: return new CMemoryMappedFile<uint8_t>();
1192  case PT_INT16: return new CMemoryMappedFile<int16_t>();
1193  case PT_UINT16: return new CMemoryMappedFile<uint16_t>();
1194  case PT_INT32: return new CMemoryMappedFile<int32_t>();
1195  case PT_UINT32: return new CMemoryMappedFile<uint32_t>();
1196  case PT_INT64: return new CMemoryMappedFile<int64_t>();
1197  case PT_UINT64: return new CMemoryMappedFile<uint64_t>();
1198  case PT_FLOAT32: return new CMemoryMappedFile<float32_t>();
1199  case PT_FLOAT64: return new CMemoryMappedFile<float64_t>();
1200  case PT_FLOATMAX: return new CMemoryMappedFile<floatmax_t>();
1201  case PT_COMPLEX128: return NULL;
1202  case PT_SGOBJECT:
1203  case PT_UNDEFINED: return NULL;
1204  }
1205  return NULL;
1206 }
1208 {
1209  switch (g)
1210  {
1211  case PT_BOOL: return new CCache<bool>();
1212  case PT_CHAR: return new CCache<char>();
1213  case PT_INT8: return new CCache<int8_t>();
1214  case PT_UINT8: return new CCache<uint8_t>();
1215  case PT_INT16: return new CCache<int16_t>();
1216  case PT_UINT16: return new CCache<uint16_t>();
1217  case PT_INT32: return new CCache<int32_t>();
1218  case PT_UINT32: return new CCache<uint32_t>();
1219  case PT_INT64: return new CCache<int64_t>();
1220  case PT_UINT64: return new CCache<uint64_t>();
1221  case PT_FLOAT32: return new CCache<float32_t>();
1222  case PT_FLOAT64: return new CCache<float64_t>();
1223  case PT_FLOATMAX: return new CCache<floatmax_t>();
1224  case PT_COMPLEX128: return NULL;
1225  case PT_SGOBJECT:
1226  case PT_UNDEFINED: return NULL;
1227  }
1228  return NULL;
1229 }
1230 static SHOGUN_TEMPLATE_CLASS CSGObject* __new_CSet(EPrimitiveType g)
1231 {
1232  switch (g)
1233  {
1234  case PT_BOOL: return new CSet<bool>();
1235  case PT_CHAR: return new CSet<char>();
1236  case PT_INT8: return new CSet<int8_t>();
1237  case PT_UINT8: return new CSet<uint8_t>();
1238  case PT_INT16: return new CSet<int16_t>();
1239  case PT_UINT16: return new CSet<uint16_t>();
1240  case PT_INT32: return new CSet<int32_t>();
1241  case PT_UINT32: return new CSet<uint32_t>();
1242  case PT_INT64: return new CSet<int64_t>();
1243  case PT_UINT64: return new CSet<uint64_t>();
1244  case PT_FLOAT32: return new CSet<float32_t>();
1245  case PT_FLOAT64: return new CSet<float64_t>();
1246  case PT_FLOATMAX: return new CSet<floatmax_t>();
1247  case PT_COMPLEX128: return NULL;
1248  case PT_SGOBJECT:
1249  case PT_UNDEFINED: return NULL;
1250  }
1251  return NULL;
1252 }
1254 {
1255  switch (g)
1256  {
1257  case PT_BOOL: return new CDynamicArray<bool>();
1258  case PT_CHAR: return new CDynamicArray<char>();
1259  case PT_INT8: return new CDynamicArray<int8_t>();
1260  case PT_UINT8: return new CDynamicArray<uint8_t>();
1261  case PT_INT16: return new CDynamicArray<int16_t>();
1262  case PT_UINT16: return new CDynamicArray<uint16_t>();
1263  case PT_INT32: return new CDynamicArray<int32_t>();
1264  case PT_UINT32: return new CDynamicArray<uint32_t>();
1265  case PT_INT64: return new CDynamicArray<int64_t>();
1266  case PT_UINT64: return new CDynamicArray<uint64_t>();
1267  case PT_FLOAT32: return new CDynamicArray<float32_t>();
1268  case PT_FLOAT64: return new CDynamicArray<float64_t>();
1269  case PT_FLOATMAX: return new CDynamicArray<floatmax_t>();
1270  case PT_COMPLEX128: return NULL;
1271  case PT_SGOBJECT:
1272  case PT_UNDEFINED: return NULL;
1273  }
1274  return NULL;
1275 }
1277 {
1278  switch (g)
1279  {
1280  case PT_BOOL: return new CTreeMachine<bool>();
1281  case PT_CHAR: return new CTreeMachine<char>();
1282  case PT_INT8: return new CTreeMachine<int8_t>();
1283  case PT_UINT8: return new CTreeMachine<uint8_t>();
1284  case PT_INT16: return new CTreeMachine<int16_t>();
1285  case PT_UINT16: return new CTreeMachine<uint16_t>();
1286  case PT_INT32: return new CTreeMachine<int32_t>();
1287  case PT_UINT32: return new CTreeMachine<uint32_t>();
1288  case PT_INT64: return new CTreeMachine<int64_t>();
1289  case PT_UINT64: return new CTreeMachine<uint64_t>();
1290  case PT_FLOAT32: return new CTreeMachine<float32_t>();
1291  case PT_FLOAT64: return new CTreeMachine<float64_t>();
1292  case PT_FLOATMAX: return new CTreeMachine<floatmax_t>();
1293  case PT_COMPLEX128: return NULL;
1294  case PT_SGOBJECT:
1295  case PT_UNDEFINED: return NULL;
1296  }
1297  return NULL;
1298 }
1300 {
1301  switch (g)
1302  {
1303  case PT_BOOL: return new CDecompressString<bool>();
1304  case PT_CHAR: return new CDecompressString<char>();
1305  case PT_INT8: return new CDecompressString<int8_t>();
1306  case PT_UINT8: return new CDecompressString<uint8_t>();
1307  case PT_INT16: return new CDecompressString<int16_t>();
1308  case PT_UINT16: return new CDecompressString<uint16_t>();
1309  case PT_INT32: return new CDecompressString<int32_t>();
1310  case PT_UINT32: return new CDecompressString<uint32_t>();
1311  case PT_INT64: return new CDecompressString<int64_t>();
1312  case PT_UINT64: return new CDecompressString<uint64_t>();
1313  case PT_FLOAT32: return new CDecompressString<float32_t>();
1314  case PT_FLOAT64: return new CDecompressString<float64_t>();
1315  case PT_FLOATMAX: return new CDecompressString<floatmax_t>();
1316  case PT_COMPLEX128: return NULL;
1317  case PT_SGOBJECT:
1318  case PT_UNDEFINED: return NULL;
1319  }
1320  return NULL;
1321 }
1323 {
1324  switch (g)
1325  {
1326  case PT_BOOL: return new CStreamingDenseFeatures<bool>();
1327  case PT_CHAR: return new CStreamingDenseFeatures<char>();
1328  case PT_INT8: return new CStreamingDenseFeatures<int8_t>();
1329  case PT_UINT8: return new CStreamingDenseFeatures<uint8_t>();
1330  case PT_INT16: return new CStreamingDenseFeatures<int16_t>();
1331  case PT_UINT16: return new CStreamingDenseFeatures<uint16_t>();
1332  case PT_INT32: return new CStreamingDenseFeatures<int32_t>();
1333  case PT_UINT32: return new CStreamingDenseFeatures<uint32_t>();
1334  case PT_INT64: return new CStreamingDenseFeatures<int64_t>();
1335  case PT_UINT64: return new CStreamingDenseFeatures<uint64_t>();
1336  case PT_FLOAT32: return new CStreamingDenseFeatures<float32_t>();
1337  case PT_FLOAT64: return new CStreamingDenseFeatures<float64_t>();
1338  case PT_FLOATMAX: return new CStreamingDenseFeatures<floatmax_t>();
1339  case PT_COMPLEX128: return NULL;
1340  case PT_SGOBJECT:
1341  case PT_UNDEFINED: return NULL;
1342  }
1343  return NULL;
1344 }
1346 {
1347  switch (g)
1348  {
1349  case PT_BOOL: return new CStreamingHashedDenseFeatures<bool>();
1350  case PT_CHAR: return new CStreamingHashedDenseFeatures<char>();
1351  case PT_INT8: return new CStreamingHashedDenseFeatures<int8_t>();
1352  case PT_UINT8: return new CStreamingHashedDenseFeatures<uint8_t>();
1353  case PT_INT16: return new CStreamingHashedDenseFeatures<int16_t>();
1354  case PT_UINT16: return new CStreamingHashedDenseFeatures<uint16_t>();
1355  case PT_INT32: return new CStreamingHashedDenseFeatures<int32_t>();
1356  case PT_UINT32: return new CStreamingHashedDenseFeatures<uint32_t>();
1357  case PT_INT64: return new CStreamingHashedDenseFeatures<int64_t>();
1358  case PT_UINT64: return new CStreamingHashedDenseFeatures<uint64_t>();
1359  case PT_FLOAT32: return new CStreamingHashedDenseFeatures<float32_t>();
1360  case PT_FLOAT64: return new CStreamingHashedDenseFeatures<float64_t>();
1361  case PT_FLOATMAX: return new CStreamingHashedDenseFeatures<floatmax_t>();
1362  case PT_COMPLEX128: return NULL;
1363  case PT_SGOBJECT:
1364  case PT_UNDEFINED: return NULL;
1365  }
1366  return NULL;
1367 }
1369 {
1370  switch (g)
1371  {
1372  case PT_BOOL: return new CStreamingHashedSparseFeatures<bool>();
1373  case PT_CHAR: return new CStreamingHashedSparseFeatures<char>();
1374  case PT_INT8: return new CStreamingHashedSparseFeatures<int8_t>();
1375  case PT_UINT8: return new CStreamingHashedSparseFeatures<uint8_t>();
1376  case PT_INT16: return new CStreamingHashedSparseFeatures<int16_t>();
1377  case PT_UINT16: return new CStreamingHashedSparseFeatures<uint16_t>();
1378  case PT_INT32: return new CStreamingHashedSparseFeatures<int32_t>();
1379  case PT_UINT32: return new CStreamingHashedSparseFeatures<uint32_t>();
1380  case PT_INT64: return new CStreamingHashedSparseFeatures<int64_t>();
1381  case PT_UINT64: return new CStreamingHashedSparseFeatures<uint64_t>();
1382  case PT_FLOAT32: return new CStreamingHashedSparseFeatures<float32_t>();
1383  case PT_FLOAT64: return new CStreamingHashedSparseFeatures<float64_t>();
1384  case PT_FLOATMAX: return new CStreamingHashedSparseFeatures<floatmax_t>();
1385  case PT_COMPLEX128: return NULL;
1386  case PT_SGOBJECT:
1387  case PT_UNDEFINED: return NULL;
1388  }
1389  return NULL;
1390 }
1392 {
1393  switch (g)
1394  {
1395  case PT_BOOL: return new CStreamingStringFeatures<bool>();
1396  case PT_CHAR: return new CStreamingStringFeatures<char>();
1397  case PT_INT8: return new CStreamingStringFeatures<int8_t>();
1398  case PT_UINT8: return new CStreamingStringFeatures<uint8_t>();
1399  case PT_INT16: return new CStreamingStringFeatures<int16_t>();
1400  case PT_UINT16: return new CStreamingStringFeatures<uint16_t>();
1401  case PT_INT32: return new CStreamingStringFeatures<int32_t>();
1402  case PT_UINT32: return new CStreamingStringFeatures<uint32_t>();
1403  case PT_INT64: return new CStreamingStringFeatures<int64_t>();
1404  case PT_UINT64: return new CStreamingStringFeatures<uint64_t>();
1405  case PT_FLOAT32: return new CStreamingStringFeatures<float32_t>();
1406  case PT_FLOAT64: return new CStreamingStringFeatures<float64_t>();
1407  case PT_FLOATMAX: return new CStreamingStringFeatures<floatmax_t>();
1408  case PT_COMPLEX128: return NULL;
1409  case PT_SGOBJECT:
1410  case PT_UNDEFINED: return NULL;
1411  }
1412  return NULL;
1413 }
1415 {
1416  switch (g)
1417  {
1418  case PT_BOOL: return new CStreamingSparseFeatures<bool>();
1419  case PT_CHAR: return new CStreamingSparseFeatures<char>();
1420  case PT_INT8: return new CStreamingSparseFeatures<int8_t>();
1421  case PT_UINT8: return new CStreamingSparseFeatures<uint8_t>();
1422  case PT_INT16: return new CStreamingSparseFeatures<int16_t>();
1423  case PT_UINT16: return new CStreamingSparseFeatures<uint16_t>();
1424  case PT_INT32: return new CStreamingSparseFeatures<int32_t>();
1425  case PT_UINT32: return new CStreamingSparseFeatures<uint32_t>();
1426  case PT_INT64: return new CStreamingSparseFeatures<int64_t>();
1427  case PT_UINT64: return new CStreamingSparseFeatures<uint64_t>();
1428  case PT_FLOAT32: return new CStreamingSparseFeatures<float32_t>();
1429  case PT_FLOAT64: return new CStreamingSparseFeatures<float64_t>();
1430  case PT_FLOATMAX: return new CStreamingSparseFeatures<floatmax_t>();
1431  case PT_COMPLEX128: return NULL;
1432  case PT_SGOBJECT:
1433  case PT_UNDEFINED: return NULL;
1434  }
1435  return NULL;
1436 }
1438 {
1439  switch (g)
1440  {
1441  case PT_BOOL: return new CSparseFeatures<bool>();
1442  case PT_CHAR: return new CSparseFeatures<char>();
1443  case PT_INT8: return new CSparseFeatures<int8_t>();
1444  case PT_UINT8: return new CSparseFeatures<uint8_t>();
1445  case PT_INT16: return new CSparseFeatures<int16_t>();
1446  case PT_UINT16: return new CSparseFeatures<uint16_t>();
1447  case PT_INT32: return new CSparseFeatures<int32_t>();
1448  case PT_UINT32: return new CSparseFeatures<uint32_t>();
1449  case PT_INT64: return new CSparseFeatures<int64_t>();
1450  case PT_UINT64: return new CSparseFeatures<uint64_t>();
1451  case PT_FLOAT32: return new CSparseFeatures<float32_t>();
1452  case PT_FLOAT64: return new CSparseFeatures<float64_t>();
1453  case PT_FLOATMAX: return new CSparseFeatures<floatmax_t>();
1454  case PT_COMPLEX128: return NULL;
1455  case PT_SGOBJECT:
1456  case PT_UNDEFINED: return NULL;
1457  }
1458  return NULL;
1459 }
1461 {
1462  switch (g)
1463  {
1464  case PT_BOOL: return new CDenseSubSamplesFeatures<bool>();
1465  case PT_CHAR: return new CDenseSubSamplesFeatures<char>();
1466  case PT_INT8: return new CDenseSubSamplesFeatures<int8_t>();
1467  case PT_UINT8: return new CDenseSubSamplesFeatures<uint8_t>();
1468  case PT_INT16: return new CDenseSubSamplesFeatures<int16_t>();
1469  case PT_UINT16: return new CDenseSubSamplesFeatures<uint16_t>();
1470  case PT_INT32: return new CDenseSubSamplesFeatures<int32_t>();
1471  case PT_UINT32: return new CDenseSubSamplesFeatures<uint32_t>();
1472  case PT_INT64: return new CDenseSubSamplesFeatures<int64_t>();
1473  case PT_UINT64: return new CDenseSubSamplesFeatures<uint64_t>();
1474  case PT_FLOAT32: return new CDenseSubSamplesFeatures<float32_t>();
1475  case PT_FLOAT64: return new CDenseSubSamplesFeatures<float64_t>();
1476  case PT_FLOATMAX: return new CDenseSubSamplesFeatures<floatmax_t>();
1477  case PT_COMPLEX128: return NULL;
1478  case PT_SGOBJECT:
1479  case PT_UNDEFINED: return NULL;
1480  }
1481  return NULL;
1482 }
1484 {
1485  switch (g)
1486  {
1487  case PT_BOOL: return new CDenseFeatures<bool>();
1488  case PT_CHAR: return new CDenseFeatures<char>();
1489  case PT_INT8: return new CDenseFeatures<int8_t>();
1490  case PT_UINT8: return new CDenseFeatures<uint8_t>();
1491  case PT_INT16: return new CDenseFeatures<int16_t>();
1492  case PT_UINT16: return new CDenseFeatures<uint16_t>();
1493  case PT_INT32: return new CDenseFeatures<int32_t>();
1494  case PT_UINT32: return new CDenseFeatures<uint32_t>();
1495  case PT_INT64: return new CDenseFeatures<int64_t>();
1496  case PT_UINT64: return new CDenseFeatures<uint64_t>();
1497  case PT_FLOAT32: return new CDenseFeatures<float32_t>();
1498  case PT_FLOAT64: return new CDenseFeatures<float64_t>();
1499  case PT_FLOATMAX: return new CDenseFeatures<floatmax_t>();
1500  case PT_COMPLEX128: return NULL;
1501  case PT_SGOBJECT:
1502  case PT_UNDEFINED: return NULL;
1503  }
1504  return NULL;
1505 }
1507 {
1508  switch (g)
1509  {
1510  case PT_BOOL: return new CStringFileFeatures<bool>();
1511  case PT_CHAR: return new CStringFileFeatures<char>();
1512  case PT_INT8: return new CStringFileFeatures<int8_t>();
1513  case PT_UINT8: return new CStringFileFeatures<uint8_t>();
1514  case PT_INT16: return new CStringFileFeatures<int16_t>();
1515  case PT_UINT16: return new CStringFileFeatures<uint16_t>();
1516  case PT_INT32: return new CStringFileFeatures<int32_t>();
1517  case PT_UINT32: return new CStringFileFeatures<uint32_t>();
1518  case PT_INT64: return new CStringFileFeatures<int64_t>();
1519  case PT_UINT64: return new CStringFileFeatures<uint64_t>();
1520  case PT_FLOAT32: return new CStringFileFeatures<float32_t>();
1521  case PT_FLOAT64: return new CStringFileFeatures<float64_t>();
1522  case PT_FLOATMAX: return new CStringFileFeatures<floatmax_t>();
1523  case PT_COMPLEX128: return NULL;
1524  case PT_SGOBJECT:
1525  case PT_UNDEFINED: return NULL;
1526  }
1527  return NULL;
1528 }
1530 {
1531  switch (g)
1532  {
1533  case PT_BOOL: return new CHashedSparseFeatures<bool>();
1534  case PT_CHAR: return new CHashedSparseFeatures<char>();
1535  case PT_INT8: return new CHashedSparseFeatures<int8_t>();
1536  case PT_UINT8: return new CHashedSparseFeatures<uint8_t>();
1537  case PT_INT16: return new CHashedSparseFeatures<int16_t>();
1538  case PT_UINT16: return new CHashedSparseFeatures<uint16_t>();
1539  case PT_INT32: return new CHashedSparseFeatures<int32_t>();
1540  case PT_UINT32: return new CHashedSparseFeatures<uint32_t>();
1541  case PT_INT64: return new CHashedSparseFeatures<int64_t>();
1542  case PT_UINT64: return new CHashedSparseFeatures<uint64_t>();
1543  case PT_FLOAT32: return new CHashedSparseFeatures<float32_t>();
1544  case PT_FLOAT64: return new CHashedSparseFeatures<float64_t>();
1545  case PT_FLOATMAX: return new CHashedSparseFeatures<floatmax_t>();
1546  case PT_COMPLEX128: return NULL;
1547  case PT_SGOBJECT:
1548  case PT_UNDEFINED: return NULL;
1549  }
1550  return NULL;
1551 }
1553 {
1554  switch (g)
1555  {
1556  case PT_BOOL: return new CHashedDenseFeatures<bool>();
1557  case PT_CHAR: return new CHashedDenseFeatures<char>();
1558  case PT_INT8: return new CHashedDenseFeatures<int8_t>();
1559  case PT_UINT8: return new CHashedDenseFeatures<uint8_t>();
1560  case PT_INT16: return new CHashedDenseFeatures<int16_t>();
1561  case PT_UINT16: return new CHashedDenseFeatures<uint16_t>();
1562  case PT_INT32: return new CHashedDenseFeatures<int32_t>();
1563  case PT_UINT32: return new CHashedDenseFeatures<uint32_t>();
1564  case PT_INT64: return new CHashedDenseFeatures<int64_t>();
1565  case PT_UINT64: return new CHashedDenseFeatures<uint64_t>();
1566  case PT_FLOAT32: return new CHashedDenseFeatures<float32_t>();
1567  case PT_FLOAT64: return new CHashedDenseFeatures<float64_t>();
1568  case PT_FLOATMAX: return new CHashedDenseFeatures<floatmax_t>();
1569  case PT_COMPLEX128: return NULL;
1570  case PT_SGOBJECT:
1571  case PT_UNDEFINED: return NULL;
1572  }
1573  return NULL;
1574 }
1576 {
1577  switch (g)
1578  {
1579  case PT_BOOL: return new CStringFeatures<bool>();
1580  case PT_CHAR: return new CStringFeatures<char>();
1581  case PT_INT8: return new CStringFeatures<int8_t>();
1582  case PT_UINT8: return new CStringFeatures<uint8_t>();
1583  case PT_INT16: return new CStringFeatures<int16_t>();
1584  case PT_UINT16: return new CStringFeatures<uint16_t>();
1585  case PT_INT32: return new CStringFeatures<int32_t>();
1586  case PT_UINT32: return new CStringFeatures<uint32_t>();
1587  case PT_INT64: return new CStringFeatures<int64_t>();
1588  case PT_UINT64: return new CStringFeatures<uint64_t>();
1589  case PT_FLOAT32: return new CStringFeatures<float32_t>();
1590  case PT_FLOAT64: return new CStringFeatures<float64_t>();
1591  case PT_FLOATMAX: return new CStringFeatures<floatmax_t>();
1592  case PT_COMPLEX128: return NULL;
1593  case PT_SGOBJECT:
1594  case PT_UNDEFINED: return NULL;
1595  }
1596  return NULL;
1597 }
1599 {
1600  switch (g)
1601  {
1602  case PT_BOOL: return new CMatrixFeatures<bool>();
1603  case PT_CHAR: return new CMatrixFeatures<char>();
1604  case PT_INT8: return new CMatrixFeatures<int8_t>();
1605  case PT_UINT8: return new CMatrixFeatures<uint8_t>();
1606  case PT_INT16: return new CMatrixFeatures<int16_t>();
1607  case PT_UINT16: return new CMatrixFeatures<uint16_t>();
1608  case PT_INT32: return new CMatrixFeatures<int32_t>();
1609  case PT_UINT32: return new CMatrixFeatures<uint32_t>();
1610  case PT_INT64: return new CMatrixFeatures<int64_t>();
1611  case PT_UINT64: return new CMatrixFeatures<uint64_t>();
1612  case PT_FLOAT32: return new CMatrixFeatures<float32_t>();
1613  case PT_FLOAT64: return new CMatrixFeatures<float64_t>();
1614  case PT_FLOATMAX: return new CMatrixFeatures<floatmax_t>();
1615  case PT_COMPLEX128: return NULL;
1616  case PT_SGOBJECT:
1617  case PT_UNDEFINED: return NULL;
1618  }
1619  return NULL;
1620 }
1622 {
1623  switch (g)
1624  {
1625  case PT_BOOL: return new CDenseSubsetFeatures<bool>();
1626  case PT_CHAR: return new CDenseSubsetFeatures<char>();
1627  case PT_INT8: return new CDenseSubsetFeatures<int8_t>();
1628  case PT_UINT8: return new CDenseSubsetFeatures<uint8_t>();
1629  case PT_INT16: return new CDenseSubsetFeatures<int16_t>();
1630  case PT_UINT16: return new CDenseSubsetFeatures<uint16_t>();
1631  case PT_INT32: return new CDenseSubsetFeatures<int32_t>();
1632  case PT_UINT32: return new CDenseSubsetFeatures<uint32_t>();
1633  case PT_INT64: return new CDenseSubsetFeatures<int64_t>();
1634  case PT_UINT64: return new CDenseSubsetFeatures<uint64_t>();
1635  case PT_FLOAT32: return new CDenseSubsetFeatures<float32_t>();
1636  case PT_FLOAT64: return new CDenseSubsetFeatures<float64_t>();
1637  case PT_FLOATMAX: return new CDenseSubsetFeatures<floatmax_t>();
1638  case PT_COMPLEX128: return NULL;
1639  case PT_SGOBJECT:
1640  case PT_UNDEFINED: return NULL;
1641  }
1642  return NULL;
1643 }
1645 {
1646  switch (g)
1647  {
1648  case PT_BOOL: return new CStoreScalarAggregator<bool>();
1649  case PT_CHAR: return new CStoreScalarAggregator<char>();
1650  case PT_INT8: return new CStoreScalarAggregator<int8_t>();
1651  case PT_UINT8: return new CStoreScalarAggregator<uint8_t>();
1652  case PT_INT16: return new CStoreScalarAggregator<int16_t>();
1653  case PT_UINT16: return new CStoreScalarAggregator<uint16_t>();
1654  case PT_INT32: return new CStoreScalarAggregator<int32_t>();
1655  case PT_UINT32: return new CStoreScalarAggregator<uint32_t>();
1656  case PT_INT64: return new CStoreScalarAggregator<int64_t>();
1657  case PT_UINT64: return new CStoreScalarAggregator<uint64_t>();
1658  case PT_FLOAT32: return new CStoreScalarAggregator<float32_t>();
1659  case PT_FLOAT64: return new CStoreScalarAggregator<float64_t>();
1660  case PT_FLOATMAX: return new CStoreScalarAggregator<floatmax_t>();
1661  case PT_COMPLEX128: return new CStoreScalarAggregator<complex128_t>();
1662  case PT_SGOBJECT:
1663  case PT_UNDEFINED: return NULL;
1664  }
1665  return NULL;
1666 }
1668 {
1669  switch (g)
1670  {
1671  case PT_BOOL: return new CVectorResult<bool>();
1672  case PT_CHAR: return new CVectorResult<char>();
1673  case PT_INT8: return new CVectorResult<int8_t>();
1674  case PT_UINT8: return new CVectorResult<uint8_t>();
1675  case PT_INT16: return new CVectorResult<int16_t>();
1676  case PT_UINT16: return new CVectorResult<uint16_t>();
1677  case PT_INT32: return new CVectorResult<int32_t>();
1678  case PT_UINT32: return new CVectorResult<uint32_t>();
1679  case PT_INT64: return new CVectorResult<int64_t>();
1680  case PT_UINT64: return new CVectorResult<uint64_t>();
1681  case PT_FLOAT32: return new CVectorResult<float32_t>();
1682  case PT_FLOAT64: return new CVectorResult<float64_t>();
1683  case PT_FLOATMAX: return new CVectorResult<floatmax_t>();
1684  case PT_COMPLEX128: return new CVectorResult<complex128_t>();
1685  case PT_SGOBJECT:
1686  case PT_UNDEFINED: return NULL;
1687  }
1688  return NULL;
1689 }
1691 {
1692  switch (g)
1693  {
1694  case PT_BOOL: return new CScalarResult<bool>();
1695  case PT_CHAR: return new CScalarResult<char>();
1696  case PT_INT8: return new CScalarResult<int8_t>();
1697  case PT_UINT8: return new CScalarResult<uint8_t>();
1698  case PT_INT16: return new CScalarResult<int16_t>();
1699  case PT_UINT16: return new CScalarResult<uint16_t>();
1700  case PT_INT32: return new CScalarResult<int32_t>();
1701  case PT_UINT32: return new CScalarResult<uint32_t>();
1702  case PT_INT64: return new CScalarResult<int64_t>();
1703  case PT_UINT64: return new CScalarResult<uint64_t>();
1704  case PT_FLOAT32: return new CScalarResult<float32_t>();
1705  case PT_FLOAT64: return new CScalarResult<float64_t>();
1706  case PT_FLOATMAX: return new CScalarResult<floatmax_t>();
1707  case PT_COMPLEX128: return new CScalarResult<complex128_t>();
1708  case PT_SGOBJECT:
1709  case PT_UNDEFINED: return NULL;
1710  }
1711  return NULL;
1712 }
1714 {
1715  switch (g)
1716  {
1717  case PT_BOOL: return new CSparseMatrixOperator<bool>();
1718  case PT_CHAR: return new CSparseMatrixOperator<char>();
1719  case PT_INT8: return new CSparseMatrixOperator<int8_t>();
1720  case PT_UINT8: return new CSparseMatrixOperator<uint8_t>();
1721  case PT_INT16: return new CSparseMatrixOperator<int16_t>();
1722  case PT_UINT16: return new CSparseMatrixOperator<uint16_t>();
1723  case PT_INT32: return new CSparseMatrixOperator<int32_t>();
1724  case PT_UINT32: return new CSparseMatrixOperator<uint32_t>();
1725  case PT_INT64: return new CSparseMatrixOperator<int64_t>();
1726  case PT_UINT64: return new CSparseMatrixOperator<uint64_t>();
1727  case PT_FLOAT32: return new CSparseMatrixOperator<float32_t>();
1728  case PT_FLOAT64: return new CSparseMatrixOperator<float64_t>();
1729  case PT_FLOATMAX: return new CSparseMatrixOperator<floatmax_t>();
1730  case PT_COMPLEX128: return new CSparseMatrixOperator<complex128_t>();
1731  case PT_SGOBJECT:
1732  case PT_UNDEFINED: return NULL;
1733  }
1734  return NULL;
1735 }
1737 {
1738  switch (g)
1739  {
1740  case PT_BOOL: return new CDenseMatrixOperator<bool>();
1741  case PT_CHAR: return new CDenseMatrixOperator<char>();
1742  case PT_INT8: return new CDenseMatrixOperator<int8_t>();
1743  case PT_UINT8: return new CDenseMatrixOperator<uint8_t>();
1744  case PT_INT16: return new CDenseMatrixOperator<int16_t>();
1745  case PT_UINT16: return new CDenseMatrixOperator<uint16_t>();
1746  case PT_INT32: return new CDenseMatrixOperator<int32_t>();
1747  case PT_UINT32: return new CDenseMatrixOperator<uint32_t>();
1748  case PT_INT64: return new CDenseMatrixOperator<int64_t>();
1749  case PT_UINT64: return new CDenseMatrixOperator<uint64_t>();
1750  case PT_FLOAT32: return new CDenseMatrixOperator<float32_t>();
1751  case PT_FLOAT64: return new CDenseMatrixOperator<float64_t>();
1752  case PT_FLOATMAX: return new CDenseMatrixOperator<floatmax_t>();
1753  case PT_COMPLEX128: return new CDenseMatrixOperator<complex128_t>();
1754  case PT_SGOBJECT:
1755  case PT_UNDEFINED: return NULL;
1756  }
1757  return NULL;
1758 }
1759 typedef CSGObject* (*new_sgserializable_t)(EPrimitiveType generic);
1760 #ifndef DOXYGEN_SHOULD_SKIP_THIS
1761 typedef struct
1762 {
1763  const char* m_class_name;
1764  new_sgserializable_t m_new_sgserializable;
1765 } class_list_entry_t;
1766 #endif
1767 
1768 static class_list_entry_t class_list[] = {
1769 {"Sequence", SHOGUN_BASIC_CLASS __new_CSequence},
1770 {"SequenceLabels", SHOGUN_BASIC_CLASS __new_CSequenceLabels},
1771 {"GraphCut", SHOGUN_BASIC_CLASS __new_CGraphCut},
1772 {"HashedMultilabelModel", SHOGUN_BASIC_CLASS __new_CHashedMultilabelModel},
1773 {"FactorType", SHOGUN_BASIC_CLASS __new_CFactorType},
1774 {"TableFactorType", SHOGUN_BASIC_CLASS __new_CTableFactorType},
1776 {"MulticlassModel", SHOGUN_BASIC_CLASS __new_CMulticlassModel},
1777 {"PlifArray", SHOGUN_BASIC_CLASS __new_CPlifArray},
1778 {"FactorDataSource", SHOGUN_BASIC_CLASS __new_CFactorDataSource},
1779 {"Factor", SHOGUN_BASIC_CLASS __new_CFactor},
1780 {"TwoStateModel", SHOGUN_BASIC_CLASS __new_CTwoStateModel},
1781 {"HierarchicalMultilabelModel", SHOGUN_BASIC_CLASS __new_CHierarchicalMultilabelModel},
1782 {"StochasticSOSVM", SHOGUN_BASIC_CLASS __new_CStochasticSOSVM},
1783 {"IntronList", SHOGUN_BASIC_CLASS __new_CIntronList},
1784 {"FWSOSVM", SHOGUN_BASIC_CLASS __new_CFWSOSVM},
1785 {"SparseMultilabel", SHOGUN_BASIC_CLASS __new_CSparseMultilabel},
1786 {"MultilabelSOLabels", SHOGUN_BASIC_CLASS __new_CMultilabelSOLabels},
1787 {"DualLibQPBMSOSVM", SHOGUN_BASIC_CLASS __new_CDualLibQPBMSOSVM},
1788 {"SOSVMHelper", SHOGUN_BASIC_CLASS __new_CSOSVMHelper},
1789 {"SegmentLoss", SHOGUN_BASIC_CLASS __new_CSegmentLoss},
1790 {"GEMPLP", SHOGUN_BASIC_CLASS __new_CGEMPLP},
1791 {"HMSVMModel", SHOGUN_BASIC_CLASS __new_CHMSVMModel},
1792 {"MultilabelModel", SHOGUN_BASIC_CLASS __new_CMultilabelModel},
1793 {"DisjointSet", SHOGUN_BASIC_CLASS __new_CDisjointSet},
1794 {"MAPInference", SHOGUN_BASIC_CLASS __new_CMAPInference},
1795 {"PlifMatrix", SHOGUN_BASIC_CLASS __new_CPlifMatrix},
1796 {"CCSOSVM", SHOGUN_BASIC_CLASS __new_CCCSOSVM},
1797 {"FactorGraph", SHOGUN_BASIC_CLASS __new_CFactorGraph},
1798 {"FactorGraphDataGenerator", SHOGUN_BASIC_CLASS __new_CFactorGraphDataGenerator},
1799 {"FactorGraphModel", SHOGUN_BASIC_CLASS __new_CFactorGraphModel},
1800 {"MultilabelCLRModel", SHOGUN_BASIC_CLASS __new_CMultilabelCLRModel},
1801 {"DynProg", SHOGUN_BASIC_CLASS __new_CDynProg},
1802 {"MulticlassSOLabels", SHOGUN_BASIC_CLASS __new_CMulticlassSOLabels},
1803 {"WeightedMajorityVote", SHOGUN_BASIC_CLASS __new_CWeightedMajorityVote},
1804 {"MeanRule", SHOGUN_BASIC_CLASS __new_CMeanRule},
1805 {"MajorityVote", SHOGUN_BASIC_CLASS __new_CMajorityVote},
1806 {"GaussianProcessRegression", SHOGUN_BASIC_CLASS __new_CGaussianProcessRegression},
1807 {"KernelRidgeRegression", SHOGUN_BASIC_CLASS __new_CKernelRidgeRegression},
1808 {"LibLinearRegression", SHOGUN_BASIC_CLASS __new_CLibLinearRegression},
1809 {"MKLRegression", SHOGUN_BASIC_CLASS __new_CMKLRegression},
1810 {"LibSVR", SHOGUN_BASIC_CLASS __new_CLibSVR},
1811 {"LeastSquaresRegression", SHOGUN_BASIC_CLASS __new_CLeastSquaresRegression},
1812 {"LinearRidgeRegression", SHOGUN_BASIC_CLASS __new_CLinearRidgeRegression},
1813 {"LeastAngleRegression", SHOGUN_BASIC_CLASS __new_CLeastAngleRegression},
1814 {"OnlineLibLinear", SHOGUN_BASIC_CLASS __new_COnlineLibLinear},
1815 {"SVMOcas", SHOGUN_BASIC_CLASS __new_CSVMOcas},
1816 {"LibSVMOneClass", SHOGUN_BASIC_CLASS __new_CLibSVMOneClass},
1818 {"OnlineSVMSGD", SHOGUN_BASIC_CLASS __new_COnlineSVMSGD},
1819 {"SVMLin", SHOGUN_BASIC_CLASS __new_CSVMLin},
1820 {"SGDQN", SHOGUN_BASIC_CLASS __new_CSGDQN},
1821 {"WDSVMOcas", SHOGUN_BASIC_CLASS __new_CWDSVMOcas},
1822 {"NewtonSVM", SHOGUN_BASIC_CLASS __new_CNewtonSVM},
1823 {"GNPPLib", SHOGUN_BASIC_CLASS __new_CGNPPLib},
1824 {"SVMSGD", SHOGUN_BASIC_CLASS __new_CSVMSGD},
1825 {"QPBSVMLib", SHOGUN_BASIC_CLASS __new_CQPBSVMLib},
1826 {"LibLinear", SHOGUN_BASIC_CLASS __new_CLibLinear},
1827 {"GPBTSVM", SHOGUN_BASIC_CLASS __new_CGPBTSVM},
1828 {"GNPPSVM", SHOGUN_BASIC_CLASS __new_CGNPPSVM},
1829 {"LibSVM", SHOGUN_BASIC_CLASS __new_CLibSVM},
1830 {"MPDSVM", SHOGUN_BASIC_CLASS __new_CMPDSVM},
1832 {"NearestCentroid", SHOGUN_BASIC_CLASS __new_CNearestCentroid},
1833 {"MKLMulticlass", SHOGUN_BASIC_CLASS __new_CMKLMulticlass},
1834 {"MKLOneClass", SHOGUN_BASIC_CLASS __new_CMKLOneClass},
1835 {"MKLClassification", SHOGUN_BASIC_CLASS __new_CMKLClassification},
1836 {"VowpalWabbit", SHOGUN_BASIC_CLASS __new_CVowpalWabbit},
1837 {"VwRegressor", SHOGUN_BASIC_CLASS __new_CVwRegressor},
1838 {"VwNativeCacheWriter", SHOGUN_BASIC_CLASS __new_CVwNativeCacheWriter},
1839 {"VwNativeCacheReader", SHOGUN_BASIC_CLASS __new_CVwNativeCacheReader},
1840 {"VwEnvironment", SHOGUN_BASIC_CLASS __new_CVwEnvironment},
1841 {"VwParser", SHOGUN_BASIC_CLASS __new_CVwParser},
1842 {"VwAdaptiveLearner", SHOGUN_BASIC_CLASS __new_CVwAdaptiveLearner},
1843 {"VwNonAdaptiveLearner", SHOGUN_BASIC_CLASS __new_CVwNonAdaptiveLearner},
1844 {"AveragedPerceptron", SHOGUN_BASIC_CLASS __new_CAveragedPerceptron},
1845 {"GaussianProcessClassification", SHOGUN_BASIC_CLASS __new_CGaussianProcessClassification},
1846 {"PluginEstimate", SHOGUN_BASIC_CLASS __new_CPluginEstimate},
1847 {"Perceptron", SHOGUN_BASIC_CLASS __new_CPerceptron},
1848 {"FeatureBlockLogisticRegression", SHOGUN_BASIC_CLASS __new_CFeatureBlockLogisticRegression},
1849 {"MinimizerContext", SHOGUN_BASIC_CLASS __new_CMinimizerContext},
1851 {"ProtobufFile", SHOGUN_BASIC_CLASS __new_CProtobufFile},
1852 {"StreamingFile", SHOGUN_BASIC_CLASS __new_CStreamingFile},
1853 {"StreamingVwCacheFile", SHOGUN_BASIC_CLASS __new_CStreamingVwCacheFile},
1854 {"StreamingFileFromFeatures", SHOGUN_BASIC_CLASS __new_CStreamingFileFromFeatures},
1855 {"StreamingVwFile", SHOGUN_BASIC_CLASS __new_CStreamingVwFile},
1856 {"StreamingAsciiFile", SHOGUN_BASIC_CLASS __new_CStreamingAsciiFile},
1857 {"BinaryFile", SHOGUN_BASIC_CLASS __new_CBinaryFile},
1858 {"NeuralNetworkFileReader", SHOGUN_BASIC_CLASS __new_CNeuralNetworkFileReader},
1859 {"LineReader", SHOGUN_BASIC_CLASS __new_CLineReader},
1860 {"LibSVMFile", SHOGUN_BASIC_CLASS __new_CLibSVMFile},
1862 {"SerializableAsciiFile", SHOGUN_BASIC_CLASS __new_CSerializableAsciiFile},
1863 {"IOBuffer", SHOGUN_BASIC_CLASS __new_CIOBuffer},
1864 {"UAIFile", SHOGUN_BASIC_CLASS __new_CUAIFile},
1865 {"Parser", SHOGUN_BASIC_CLASS __new_CParser},
1866 {"CSVFile", SHOGUN_BASIC_CLASS __new_CCSVFile},
1868 {"DelimiterTokenizer", SHOGUN_BASIC_CLASS __new_CDelimiterTokenizer},
1869 {"Compressor", SHOGUN_BASIC_CLASS __new_CCompressor},
1870 {"IndexBlockGroup", SHOGUN_BASIC_CLASS __new_CIndexBlockGroup},
1871 {"BitString", SHOGUN_BASIC_CLASS __new_CBitString},
1873 {"JobResult", SHOGUN_BASIC_CLASS __new_CJobResult},
1874 {"SerialComputationEngine", SHOGUN_BASIC_CLASS __new_CSerialComputationEngine},
1875 {"StructuredData", SHOGUN_BASIC_CLASS __new_CStructuredData},
1876 {"Signal", SHOGUN_BASIC_CLASS __new_CSignal},
1877 {"IndexBlockTree", SHOGUN_BASIC_CLASS __new_CIndexBlockTree},
1878 {"CircularBuffer", SHOGUN_BASIC_CLASS __new_CCircularBuffer},
1879 {"IndexBlock", SHOGUN_BASIC_CLASS __new_CIndexBlock},
1881 {"NGramTokenizer", SHOGUN_BASIC_CLASS __new_CNGramTokenizer},
1882 {"ListElement", SHOGUN_BASIC_CLASS __new_CListElement},
1884 {"DynamicObjectArray", SHOGUN_BASIC_CLASS __new_CDynamicObjectArray},
1885 {"DiffusionMaps", SHOGUN_BASIC_CLASS __new_CDiffusionMaps},
1886 {"NeighborhoodPreservingEmbedding", SHOGUN_BASIC_CLASS __new_CNeighborhoodPreservingEmbedding},
1887 {"StochasticProximityEmbedding", SHOGUN_BASIC_CLASS __new_CStochasticProximityEmbedding},
1889 {"JediSep", SHOGUN_BASIC_CLASS __new_CJediSep},
1890 {"UWedgeSep", SHOGUN_BASIC_CLASS __new_CUWedgeSep},
1892 {"FFSep", SHOGUN_BASIC_CLASS __new_CFFSep},
1893 {"FastICA", SHOGUN_BASIC_CLASS __new_CFastICA},
1894 {"MultidimensionalScaling", SHOGUN_BASIC_CLASS __new_CMultidimensionalScaling},
1895 {"LaplacianEigenmaps", SHOGUN_BASIC_CLASS __new_CLaplacianEigenmaps},
1896 {"HashedDocConverter", SHOGUN_BASIC_CLASS __new_CHashedDocConverter},
1897 {"HessianLocallyLinearEmbedding", SHOGUN_BASIC_CLASS __new_CHessianLocallyLinearEmbedding},
1898 {"ManifoldSculpting", SHOGUN_BASIC_CLASS __new_CManifoldSculpting},
1899 {"LocalityPreservingProjections", SHOGUN_BASIC_CLASS __new_CLocalityPreservingProjections},
1900 {"FactorAnalysis", SHOGUN_BASIC_CLASS __new_CFactorAnalysis},
1901 {"KernelLocallyLinearEmbedding", SHOGUN_BASIC_CLASS __new_CKernelLocallyLinearEmbedding},
1902 {"LinearLocalTangentSpaceAlignment", SHOGUN_BASIC_CLASS __new_CLinearLocalTangentSpaceAlignment},
1903 {"LocallyLinearEmbedding", SHOGUN_BASIC_CLASS __new_CLocallyLinearEmbedding},
1904 {"TDistributedStochasticNeighborEmbedding", SHOGUN_BASIC_CLASS __new_CTDistributedStochasticNeighborEmbedding},
1905 {"Isomap", SHOGUN_BASIC_CLASS __new_CIsomap},
1906 {"LocalTangentSpaceAlignment", SHOGUN_BASIC_CLASS __new_CLocalTangentSpaceAlignment},
1907 {"RandomSearchModelSelection", SHOGUN_BASIC_CLASS __new_CRandomSearchModelSelection},
1908 {"ModelSelectionParameters", SHOGUN_BASIC_CLASS __new_CModelSelectionParameters},
1909 {"ParameterCombination", SHOGUN_BASIC_CLASS __new_CParameterCombination},
1910 {"GradientModelSelection", SHOGUN_BASIC_CLASS __new_CGradientModelSelection},
1911 {"GridSearchModelSelection", SHOGUN_BASIC_CLASS __new_CGridSearchModelSelection},
1912 {"GMNPLib", SHOGUN_BASIC_CLASS __new_CGMNPLib},
1913 {"MulticlassTreeGuidedLogisticRegression", SHOGUN_BASIC_CLASS __new_CMulticlassTreeGuidedLogisticRegression},
1914 {"LaRank", SHOGUN_BASIC_CLASS __new_CLaRank},
1915 {"ECOCForestEncoder", SHOGUN_BASIC_CLASS __new_CECOCForestEncoder},
1916 {"ECOCRandomDenseEncoder", SHOGUN_BASIC_CLASS __new_CECOCRandomDenseEncoder},
1917 {"ECOCAEDDecoder", SHOGUN_BASIC_CLASS __new_CECOCAEDDecoder},
1918 {"ECOCDiscriminantEncoder", SHOGUN_BASIC_CLASS __new_CECOCDiscriminantEncoder},
1919 {"ECOCEDDecoder", SHOGUN_BASIC_CLASS __new_CECOCEDDecoder},
1920 {"ECOCOVREncoder", SHOGUN_BASIC_CLASS __new_CECOCOVREncoder},
1921 {"ECOCIHDDecoder", SHOGUN_BASIC_CLASS __new_CECOCIHDDecoder},
1922 {"ECOCHDDecoder", SHOGUN_BASIC_CLASS __new_CECOCHDDecoder},
1923 {"ECOCRandomSparseEncoder", SHOGUN_BASIC_CLASS __new_CECOCRandomSparseEncoder},
1924 {"ECOCLLBDecoder", SHOGUN_BASIC_CLASS __new_CECOCLLBDecoder},
1925 {"ECOCOVOEncoder", SHOGUN_BASIC_CLASS __new_CECOCOVOEncoder},
1926 {"ECOCStrategy", SHOGUN_BASIC_CLASS __new_CECOCStrategy},
1927 {"ShareBoost", SHOGUN_BASIC_CLASS __new_CShareBoost},
1928 {"MulticlassLogisticRegression", SHOGUN_BASIC_CLASS __new_CMulticlassLogisticRegression},
1929 {"MulticlassOneVsRestStrategy", SHOGUN_BASIC_CLASS __new_CMulticlassOneVsRestStrategy},
1930 {"GMNPSVM", SHOGUN_BASIC_CLASS __new_CGMNPSVM},
1932 {"MulticlassSVM", SHOGUN_BASIC_CLASS __new_CMulticlassSVM},
1933 {"MulticlassOCAS", SHOGUN_BASIC_CLASS __new_CMulticlassOCAS},
1934 {"MulticlassLibLinear", SHOGUN_BASIC_CLASS __new_CMulticlassLibLinear},
1935 {"MulticlassLibSVM", SHOGUN_BASIC_CLASS __new_CMulticlassLibSVM},
1936 {"ID3ClassifierTree", SHOGUN_BASIC_CLASS __new_CID3ClassifierTree},
1937 {"RelaxedTree", SHOGUN_BASIC_CLASS __new_CRelaxedTree},
1938 {"BalancedConditionalProbabilityTree", SHOGUN_BASIC_CLASS __new_CBalancedConditionalProbabilityTree},
1939 {"CARTree", SHOGUN_BASIC_CLASS __new_CCARTree},
1940 {"CHAIDTree", SHOGUN_BASIC_CLASS __new_CCHAIDTree},
1941 {"RandomConditionalProbabilityTree", SHOGUN_BASIC_CLASS __new_CRandomConditionalProbabilityTree},
1942 {"C45ClassifierTree", SHOGUN_BASIC_CLASS __new_CC45ClassifierTree},
1943 {"KDTree", SHOGUN_BASIC_CLASS __new_CKDTree},
1944 {"RandomCARTree", SHOGUN_BASIC_CLASS __new_CRandomCARTree},
1945 {"BallTree", SHOGUN_BASIC_CLASS __new_CBallTree},
1946 {"ThresholdRejectionStrategy", SHOGUN_BASIC_CLASS __new_CThresholdRejectionStrategy},
1947 {"DixonQTestRejectionStrategy", SHOGUN_BASIC_CLASS __new_CDixonQTestRejectionStrategy},
1948 {"MulticlassOneVsOneStrategy", SHOGUN_BASIC_CLASS __new_CMulticlassOneVsOneStrategy},
1949 {"ScatterSVM", SHOGUN_BASIC_CLASS __new_CScatterSVM},
1951 {"MCLDA", SHOGUN_BASIC_CLASS __new_CMCLDA},
1952 {"GaussianNaiveBayes", SHOGUN_BASIC_CLASS __new_CGaussianNaiveBayes},
1953 {"ManhattanWordDistance", SHOGUN_BASIC_CLASS __new_CManhattanWordDistance},
1954 {"ChebyshewMetric", SHOGUN_BASIC_CLASS __new_CChebyshewMetric},
1955 {"JensenMetric", SHOGUN_BASIC_CLASS __new_CJensenMetric},
1956 {"ChiSquareDistance", SHOGUN_BASIC_CLASS __new_CChiSquareDistance},
1957 {"ManhattanMetric", SHOGUN_BASIC_CLASS __new_CManhattanMetric},
1958 {"SparseEuclideanDistance", SHOGUN_BASIC_CLASS __new_CSparseEuclideanDistance},
1959 {"TanimotoDistance", SHOGUN_BASIC_CLASS __new_CTanimotoDistance},
1960 {"KernelDistance", SHOGUN_BASIC_CLASS __new_CKernelDistance},
1961 {"CustomDistance", SHOGUN_BASIC_CLASS __new_CCustomDistance},
1962 {"BrayCurtisDistance", SHOGUN_BASIC_CLASS __new_CBrayCurtisDistance},
1963 {"CanberraWordDistance", SHOGUN_BASIC_CLASS __new_CCanberraWordDistance},
1964 {"CustomMahalanobisDistance", SHOGUN_BASIC_CLASS __new_CCustomMahalanobisDistance},
1965 {"HammingWordDistance", SHOGUN_BASIC_CLASS __new_CHammingWordDistance},
1966 {"CosineDistance", SHOGUN_BASIC_CLASS __new_CCosineDistance},
1967 {"MahalanobisDistance", SHOGUN_BASIC_CLASS __new_CMahalanobisDistance},
1968 {"MinkowskiMetric", SHOGUN_BASIC_CLASS __new_CMinkowskiMetric},
1969 {"AttenuatedEuclideanDistance", SHOGUN_BASIC_CLASS __new_CAttenuatedEuclideanDistance},
1970 {"EuclideanDistance", SHOGUN_BASIC_CLASS __new_CEuclideanDistance},
1971 {"GeodesicMetric", SHOGUN_BASIC_CLASS __new_CGeodesicMetric},
1972 {"CanberraMetric", SHOGUN_BASIC_CLASS __new_CCanberraMetric},
1973 {"KernelStructuredOutputMachine", SHOGUN_BASIC_CLASS __new_CKernelStructuredOutputMachine},
1974 {"RandomForest", SHOGUN_BASIC_CLASS __new_CRandomForest},
1975 {"GaussianProcessMachine", SHOGUN_BASIC_CLASS __new_CGaussianProcessMachine},
1976 {"Machine", SHOGUN_BASIC_CLASS __new_CMachine},
1977 {"DistanceMachine", SHOGUN_BASIC_CLASS __new_CDistanceMachine},
1978 {"LinearStructuredOutputMachine", SHOGUN_BASIC_CLASS __new_CLinearStructuredOutputMachine},
1979 {"OnlineLinearMachine", SHOGUN_BASIC_CLASS __new_COnlineLinearMachine},
1980 {"KernelMulticlassMachine", SHOGUN_BASIC_CLASS __new_CKernelMulticlassMachine},
1981 {"NativeMulticlassMachine", SHOGUN_BASIC_CLASS __new_CNativeMulticlassMachine},
1982 {"SoftMaxLikelihood", SHOGUN_BASIC_CLASS __new_CSoftMaxLikelihood},
1983 {"SingleFITCLaplacianInferenceMethod", SHOGUN_BASIC_CLASS __new_CSingleFITCLaplacianInferenceMethod},
1984 {"StudentsTLikelihood", SHOGUN_BASIC_CLASS __new_CStudentsTLikelihood},
1985 {"ProbitVGLikelihood", SHOGUN_BASIC_CLASS __new_CProbitVGLikelihood},
1986 {"GaussianLikelihood", SHOGUN_BASIC_CLASS __new_CGaussianLikelihood},
1987 {"KLDualInferenceMethod", SHOGUN_BASIC_CLASS __new_CKLDualInferenceMethod},
1988 {"SingleLaplacianInferenceMethodWithLBFGS", SHOGUN_BASIC_CLASS __new_CSingleLaplacianInferenceMethodWithLBFGS},
1989 {"GaussianARDSparseKernel", SHOGUN_BASIC_CLASS __new_CGaussianARDSparseKernel},
1990 {"SingleFITCLaplacianInferenceMethodWithLBFGS", SHOGUN_BASIC_CLASS __new_CSingleFITCLaplacianInferenceMethodWithLBFGS},
1991 {"KLCholeskyInferenceMethod", SHOGUN_BASIC_CLASS __new_CKLCholeskyInferenceMethod},
1992 {"KLApproxDiagonalInferenceMethod", SHOGUN_BASIC_CLASS __new_CKLApproxDiagonalInferenceMethod},
1993 {"StudentsTVGLikelihood", SHOGUN_BASIC_CLASS __new_CStudentsTVGLikelihood},
1994 {"SparseVGInferenceMethod", SHOGUN_BASIC_CLASS __new_CSparseVGInferenceMethod},
1995 {"SingleLaplacianInferenceMethod", SHOGUN_BASIC_CLASS __new_CSingleLaplacianInferenceMethod},
1996 {"LogitVGLikelihood", SHOGUN_BASIC_CLASS __new_CLogitVGLikelihood},
1997 {"EPInferenceMethod", SHOGUN_BASIC_CLASS __new_CEPInferenceMethod},
1998 {"MultiLaplacianInferenceMethod", SHOGUN_BASIC_CLASS __new_CMultiLaplacianInferenceMethod},
1999 {"LogitLikelihood", SHOGUN_BASIC_CLASS __new_CLogitLikelihood},
2000 {"ZeroMean", SHOGUN_BASIC_CLASS __new_CZeroMean},
2001 {"LogitDVGLikelihood", SHOGUN_BASIC_CLASS __new_CLogitDVGLikelihood},
2002 {"LogitVGPiecewiseBoundLikelihood", SHOGUN_BASIC_CLASS __new_CLogitVGPiecewiseBoundLikelihood},
2003 {"ExactInferenceMethod", SHOGUN_BASIC_CLASS __new_CExactInferenceMethod},
2004 {"ProbitLikelihood", SHOGUN_BASIC_CLASS __new_CProbitLikelihood},
2005 {"KLCovarianceInferenceMethod", SHOGUN_BASIC_CLASS __new_CKLCovarianceInferenceMethod},
2006 {"ConstMean", SHOGUN_BASIC_CLASS __new_CConstMean},
2007 {"FITCInferenceMethod", SHOGUN_BASIC_CLASS __new_CFITCInferenceMethod},
2008 {"BaseMulticlassMachine", SHOGUN_BASIC_CLASS __new_CBaseMulticlassMachine},
2009 {"LinearMachine", SHOGUN_BASIC_CLASS __new_CLinearMachine},
2010 {"StructuredOutputMachine", SHOGUN_BASIC_CLASS __new_CStructuredOutputMachine},
2011 {"LinearMulticlassMachine", SHOGUN_BASIC_CLASS __new_CLinearMulticlassMachine},
2012 {"KernelMachine", SHOGUN_BASIC_CLASS __new_CKernelMachine},
2013 {"BaggingMachine", SHOGUN_BASIC_CLASS __new_CBaggingMachine},
2014 {"StochasticGBMachine", SHOGUN_BASIC_CLASS __new_CStochasticGBMachine},
2015 {"MultitaskClusteredLogisticRegression", SHOGUN_BASIC_CLASS __new_CMultitaskClusteredLogisticRegression},
2016 {"LibLinearMTL", SHOGUN_BASIC_CLASS __new_CLibLinearMTL},
2017 {"MultitaskKernelMaskPairNormalizer", SHOGUN_BASIC_CLASS __new_CMultitaskKernelMaskPairNormalizer},
2020 {"Taxonomy", SHOGUN_BASIC_CLASS __new_CTaxonomy},
2021 {"MultitaskKernelTreeNormalizer", SHOGUN_BASIC_CLASS __new_CMultitaskKernelTreeNormalizer},
2022 {"MultitaskTraceLogisticRegression", SHOGUN_BASIC_CLASS __new_CMultitaskTraceLogisticRegression},
2023 {"MultitaskKernelNormalizer", SHOGUN_BASIC_CLASS __new_CMultitaskKernelNormalizer},
2024 {"TaskTree", SHOGUN_BASIC_CLASS __new_CTaskTree},
2025 {"MultitaskL12LogisticRegression", SHOGUN_BASIC_CLASS __new_CMultitaskL12LogisticRegression},
2026 {"MultitaskKernelPlifNormalizer", SHOGUN_BASIC_CLASS __new_CMultitaskKernelPlifNormalizer},
2027 {"MultitaskLeastSquaresRegression", SHOGUN_BASIC_CLASS __new_CMultitaskLeastSquaresRegression},
2028 {"TaskGroup", SHOGUN_BASIC_CLASS __new_CTaskGroup},
2029 {"MultitaskKernelMaskNormalizer", SHOGUN_BASIC_CLASS __new_CMultitaskKernelMaskNormalizer},
2030 {"MultitaskLogisticRegression", SHOGUN_BASIC_CLASS __new_CMultitaskLogisticRegression},
2031 {"MultitaskROCEvaluation", SHOGUN_BASIC_CLASS __new_CMultitaskROCEvaluation},
2032 {"MultitaskLinearMachine", SHOGUN_BASIC_CLASS __new_CMultitaskLinearMachine},
2033 {"DomainAdaptationMulticlassLibLinear", SHOGUN_BASIC_CLASS __new_CDomainAdaptationMulticlassLibLinear},
2034 {"DomainAdaptationSVMLinear", SHOGUN_BASIC_CLASS __new_CDomainAdaptationSVMLinear},
2035 {"GUIFeatures", SHOGUN_BASIC_CLASS __new_CGUIFeatures},
2036 {"GUIMath", SHOGUN_BASIC_CLASS __new_CGUIMath},
2037 {"GUIPreprocessor", SHOGUN_BASIC_CLASS __new_CGUIPreprocessor},
2038 {"GUIHMM", SHOGUN_BASIC_CLASS __new_CGUIHMM},
2039 {"GUIDistance", SHOGUN_BASIC_CLASS __new_CGUIDistance},
2040 {"GUITime", SHOGUN_BASIC_CLASS __new_CGUITime},
2041 {"GUIConverter", SHOGUN_BASIC_CLASS __new_CGUIConverter},
2042 {"GUIStructure", SHOGUN_BASIC_CLASS __new_CGUIStructure},
2043 {"GUIKernel", SHOGUN_BASIC_CLASS __new_CGUIKernel},
2044 {"GUIPluginEstimate", SHOGUN_BASIC_CLASS __new_CGUIPluginEstimate},
2045 {"GUILabels", SHOGUN_BASIC_CLASS __new_CGUILabels},
2046 {"GUIClassifier", SHOGUN_BASIC_CLASS __new_CGUIClassifier},
2048 {"Gaussian", SHOGUN_BASIC_CLASS __new_CGaussian},
2049 {"Histogram", SHOGUN_BASIC_CLASS __new_CHistogram},
2050 {"GaussianDistribution", SHOGUN_BASIC_CLASS __new_CGaussianDistribution},
2051 {"PositionalPWM", SHOGUN_BASIC_CLASS __new_CPositionalPWM},
2052 {"MixtureModel", SHOGUN_BASIC_CLASS __new_CMixtureModel},
2053 {"KernelDensity", SHOGUN_BASIC_CLASS __new_CKernelDensity},
2054 {"LinearHMM", SHOGUN_BASIC_CLASS __new_CLinearHMM},
2055 {"EMMixtureModel", SHOGUN_BASIC_CLASS __new_CEMMixtureModel},
2056 {"SparseInverseCovariance", SHOGUN_BASIC_CLASS __new_CSparseInverseCovariance},
2057 {"QDiag", SHOGUN_BASIC_CLASS __new_CQDiag},
2058 {"UWedge", SHOGUN_BASIC_CLASS __new_CUWedge},
2059 {"JediDiag", SHOGUN_BASIC_CLASS __new_CJediDiag},
2060 {"JADiag", SHOGUN_BASIC_CLASS __new_CJADiag},
2061 {"FFDiag", SHOGUN_BASIC_CLASS __new_CFFDiag},
2062 {"JADiagOrth", SHOGUN_BASIC_CLASS __new_CJADiagOrth},
2063 {"Statistics", SHOGUN_BASIC_CLASS __new_CStatistics},
2064 {"Random", SHOGUN_BASIC_CLASS __new_CRandom},
2066 {"JacobiEllipticFunctions", SHOGUN_BASIC_CLASS __new_CJacobiEllipticFunctions},
2067 {"Integration", SHOGUN_BASIC_CLASS __new_CIntegration},
2068 {"DirectLinearSolverComplex", SHOGUN_BASIC_CLASS __new_CDirectLinearSolverComplex},
2069 {"ConjugateGradientSolver", SHOGUN_BASIC_CLASS __new_CConjugateGradientSolver},
2070 {"DirectSparseLinearSolver", SHOGUN_BASIC_CLASS __new_CDirectSparseLinearSolver},
2071 {"NormalSampler", SHOGUN_BASIC_CLASS __new_CNormalSampler},
2072 {"ProbingSampler", SHOGUN_BASIC_CLASS __new_CProbingSampler},
2073 {"LogDetEstimator", SHOGUN_BASIC_CLASS __new_CLogDetEstimator},
2074 {"DenseExactLogJob", SHOGUN_BASIC_CLASS __new_CDenseExactLogJob},
2075 {"RationalApproximationIndividualJob", SHOGUN_BASIC_CLASS __new_CRationalApproximationIndividualJob},
2076 {"RationalApproximationCGMJob", SHOGUN_BASIC_CLASS __new_CRationalApproximationCGMJob},
2077 {"IndividualJobResultAggregator", SHOGUN_BASIC_CLASS __new_CIndividualJobResultAggregator},
2078 {"DenseMatrixExactLog", SHOGUN_BASIC_CLASS __new_CDenseMatrixExactLog},
2079 {"LogRationalApproximationCGM", SHOGUN_BASIC_CLASS __new_CLogRationalApproximationCGM},
2080 {"LogRationalApproximationIndividual", SHOGUN_BASIC_CLASS __new_CLogRationalApproximationIndividual},
2081 {"LanczosEigenSolver", SHOGUN_BASIC_CLASS __new_CLanczosEigenSolver},
2082 {"DirectEigenSolver", SHOGUN_BASIC_CLASS __new_CDirectEigenSolver},
2083 {"NeuralSoftmaxLayer", SHOGUN_BASIC_CLASS __new_CNeuralSoftmaxLayer},
2084 {"NeuralLinearLayer", SHOGUN_BASIC_CLASS __new_CNeuralLinearLayer},
2085 {"NeuralConvolutionalLayer", SHOGUN_BASIC_CLASS __new_CNeuralConvolutionalLayer},
2086 {"DeepAutoencoder", SHOGUN_BASIC_CLASS __new_CDeepAutoencoder},
2087 {"NeuralNetwork", SHOGUN_BASIC_CLASS __new_CNeuralNetwork},
2088 {"NeuralRectifiedLinearLayer", SHOGUN_BASIC_CLASS __new_CNeuralRectifiedLinearLayer},
2089 {"NeuralLayers", SHOGUN_BASIC_CLASS __new_CNeuralLayers},
2090 {"NeuralLayer", SHOGUN_BASIC_CLASS __new_CNeuralLayer},
2091 {"DeepBeliefNetwork", SHOGUN_BASIC_CLASS __new_CDeepBeliefNetwork},
2092 {"NeuralInputLayer", SHOGUN_BASIC_CLASS __new_CNeuralInputLayer},
2093 {"NeuralLogisticLayer", SHOGUN_BASIC_CLASS __new_CNeuralLogisticLayer},
2094 {"Autoencoder", SHOGUN_BASIC_CLASS __new_CAutoencoder},
2095 {"NeuralLeakyRectifiedLinearLayer", SHOGUN_BASIC_CLASS __new_CNeuralLeakyRectifiedLinearLayer},
2097 {"ROCEvaluation", SHOGUN_BASIC_CLASS __new_CROCEvaluation},
2098 {"GradientCriterion", SHOGUN_BASIC_CLASS __new_CGradientCriterion},
2099 {"MultilabelAccuracy", SHOGUN_BASIC_CLASS __new_CMultilabelAccuracy},
2100 {"GradientResult", SHOGUN_BASIC_CLASS __new_CGradientResult},
2101 {"MulticlassAccuracy", SHOGUN_BASIC_CLASS __new_CMulticlassAccuracy},
2102 {"CrossValidationPrintOutput", SHOGUN_BASIC_CLASS __new_CCrossValidationPrintOutput},
2103 {"CrossValidationMKLStorage", SHOGUN_BASIC_CLASS __new_CCrossValidationMKLStorage},
2104 {"MeanSquaredError", SHOGUN_BASIC_CLASS __new_CMeanSquaredError},
2105 {"GradientEvaluation", SHOGUN_BASIC_CLASS __new_CGradientEvaluation},
2106 {"MeanAbsoluteError", SHOGUN_BASIC_CLASS __new_CMeanAbsoluteError},
2107 {"MulticlassOVREvaluation", SHOGUN_BASIC_CLASS __new_CMulticlassOVREvaluation},
2108 {"CrossValidationSplitting", SHOGUN_BASIC_CLASS __new_CCrossValidationSplitting},
2109 {"MeanSquaredLogError", SHOGUN_BASIC_CLASS __new_CMeanSquaredLogError},
2110 {"CrossValidationResult", SHOGUN_BASIC_CLASS __new_CCrossValidationResult},
2111 {"CrossValidation", SHOGUN_BASIC_CLASS __new_CCrossValidation},
2112 {"ClusteringAccuracy", SHOGUN_BASIC_CLASS __new_CClusteringAccuracy},
2113 {"StratifiedCrossValidationSplitting", SHOGUN_BASIC_CLASS __new_CStratifiedCrossValidationSplitting},
2114 {"PRCEvaluation", SHOGUN_BASIC_CLASS __new_CPRCEvaluation},
2115 {"StructuredAccuracy", SHOGUN_BASIC_CLASS __new_CStructuredAccuracy},
2116 {"ClusteringMutualInformation", SHOGUN_BASIC_CLASS __new_CClusteringMutualInformation},
2117 {"ContingencyTableEvaluation", SHOGUN_BASIC_CLASS __new_CContingencyTableEvaluation},
2118 {"AccuracyMeasure", SHOGUN_BASIC_CLASS __new_CAccuracyMeasure},
2119 {"ErrorRateMeasure", SHOGUN_BASIC_CLASS __new_CErrorRateMeasure},
2120 {"BALMeasure", SHOGUN_BASIC_CLASS __new_CBALMeasure},
2121 {"WRACCMeasure", SHOGUN_BASIC_CLASS __new_CWRACCMeasure},
2122 {"F1Measure", SHOGUN_BASIC_CLASS __new_CF1Measure},
2123 {"CrossCorrelationMeasure", SHOGUN_BASIC_CLASS __new_CCrossCorrelationMeasure},
2124 {"RecallMeasure", SHOGUN_BASIC_CLASS __new_CRecallMeasure},
2125 {"PrecisionMeasure", SHOGUN_BASIC_CLASS __new_CPrecisionMeasure},
2126 {"SpecificityMeasure", SHOGUN_BASIC_CLASS __new_CSpecificityMeasure},
2127 {"CrossValidationMulticlassStorage", SHOGUN_BASIC_CLASS __new_CCrossValidationMulticlassStorage},
2128 {"LOOCrossValidationSplitting", SHOGUN_BASIC_CLASS __new_CLOOCrossValidationSplitting},
2129 {"Hierarchical", SHOGUN_BASIC_CLASS __new_CHierarchical},
2131 {"KMeans", SHOGUN_BASIC_CLASS __new_CKMeans},
2132 {"LatentSOSVM", SHOGUN_BASIC_CLASS __new_CLatentSOSVM},
2133 {"LatentSVM", SHOGUN_BASIC_CLASS __new_CLatentSVM},
2135 {"LMNNStatistics", SHOGUN_BASIC_CLASS __new_CLMNNStatistics},
2136 {"FactorGraphObservation", SHOGUN_BASIC_CLASS __new_CFactorGraphObservation},
2137 {"FactorGraphLabels", SHOGUN_BASIC_CLASS __new_CFactorGraphLabels},
2138 {"LabelsFactory", SHOGUN_BASIC_CLASS __new_CLabelsFactory},
2139 {"RegressionLabels", SHOGUN_BASIC_CLASS __new_CRegressionLabels},
2140 {"MultilabelLabels", SHOGUN_BASIC_CLASS __new_CMultilabelLabels},
2141 {"LatentLabels", SHOGUN_BASIC_CLASS __new_CLatentLabels},
2142 {"StructuredLabels", SHOGUN_BASIC_CLASS __new_CStructuredLabels},
2143 {"BinaryLabels", SHOGUN_BASIC_CLASS __new_CBinaryLabels},
2144 {"MulticlassLabels", SHOGUN_BASIC_CLASS __new_CMulticlassLabels},
2146 {"FisherLDA", SHOGUN_BASIC_CLASS __new_CFisherLDA},
2147 {"PNorm", SHOGUN_BASIC_CLASS __new_CPNorm},
2148 {"HomogeneousKernelMap", SHOGUN_BASIC_CLASS __new_CHomogeneousKernelMap},
2149 {"SortWordString", SHOGUN_BASIC_CLASS __new_CSortWordString},
2150 {"SortUlongString", SHOGUN_BASIC_CLASS __new_CSortUlongString},
2151 {"PruneVarSubMean", SHOGUN_BASIC_CLASS __new_CPruneVarSubMean},
2152 {"RescaleFeatures", SHOGUN_BASIC_CLASS __new_CRescaleFeatures},
2153 {"SumOne", SHOGUN_BASIC_CLASS __new_CSumOne},
2154 {"LogPlusOne", SHOGUN_BASIC_CLASS __new_CLogPlusOne},
2155 {"BAHSIC", SHOGUN_BASIC_CLASS __new_CBAHSIC},
2156 {"NormOne", SHOGUN_BASIC_CLASS __new_CNormOne},
2157 {"RandomFourierGaussPreproc", SHOGUN_BASIC_CLASS __new_CRandomFourierGaussPreproc},
2158 {"KernelPCA", SHOGUN_BASIC_CLASS __new_CKernelPCA},
2159 {"DimensionReductionPreprocessor", SHOGUN_BASIC_CLASS __new_CDimensionReductionPreprocessor},
2160 {"ExponentialLoss", SHOGUN_BASIC_CLASS __new_CExponentialLoss},
2161 {"LogLossMargin", SHOGUN_BASIC_CLASS __new_CLogLossMargin},
2162 {"SquaredHingeLoss", SHOGUN_BASIC_CLASS __new_CSquaredHingeLoss},
2163 {"SmoothHingeLoss", SHOGUN_BASIC_CLASS __new_CSmoothHingeLoss},
2164 {"HuberLoss", SHOGUN_BASIC_CLASS __new_CHuberLoss},
2165 {"SquaredLoss", SHOGUN_BASIC_CLASS __new_CSquaredLoss},
2166 {"AbsoluteDeviationLoss", SHOGUN_BASIC_CLASS __new_CAbsoluteDeviationLoss},
2167 {"HingeLoss", SHOGUN_BASIC_CLASS __new_CHingeLoss},
2168 {"LogLoss", SHOGUN_BASIC_CLASS __new_CLogLoss},
2169 {"SigmoidKernel", SHOGUN_BASIC_CLASS __new_CSigmoidKernel},
2170 {"CircularKernel", SHOGUN_BASIC_CLASS __new_CCircularKernel},
2171 {"WeightedDegreeRBFKernel", SHOGUN_BASIC_CLASS __new_CWeightedDegreeRBFKernel},
2172 {"SphericalKernel", SHOGUN_BASIC_CLASS __new_CSphericalKernel},
2173 {"MultiquadricKernel", SHOGUN_BASIC_CLASS __new_CMultiquadricKernel},
2174 {"PolyKernel", SHOGUN_BASIC_CLASS __new_CPolyKernel},
2175 {"GaussianARDKernel", SHOGUN_BASIC_CLASS __new_CGaussianARDKernel},
2176 {"RationalQuadraticKernel", SHOGUN_BASIC_CLASS __new_CRationalQuadraticKernel},
2177 {"JensenShannonKernel", SHOGUN_BASIC_CLASS __new_CJensenShannonKernel},
2178 {"IdentityKernelNormalizer", SHOGUN_BASIC_CLASS __new_CIdentityKernelNormalizer},
2179 {"RidgeKernelNormalizer", SHOGUN_BASIC_CLASS __new_CRidgeKernelNormalizer},
2180 {"ZeroMeanCenterKernelNormalizer", SHOGUN_BASIC_CLASS __new_CZeroMeanCenterKernelNormalizer},
2181 {"SqrtDiagKernelNormalizer", SHOGUN_BASIC_CLASS __new_CSqrtDiagKernelNormalizer},
2182 {"FirstElementKernelNormalizer", SHOGUN_BASIC_CLASS __new_CFirstElementKernelNormalizer},
2183 {"DiceKernelNormalizer", SHOGUN_BASIC_CLASS __new_CDiceKernelNormalizer},
2184 {"ScatterKernelNormalizer", SHOGUN_BASIC_CLASS __new_CScatterKernelNormalizer},
2185 {"AvgDiagKernelNormalizer", SHOGUN_BASIC_CLASS __new_CAvgDiagKernelNormalizer},
2186 {"VarianceKernelNormalizer", SHOGUN_BASIC_CLASS __new_CVarianceKernelNormalizer},
2187 {"TanimotoKernelNormalizer", SHOGUN_BASIC_CLASS __new_CTanimotoKernelNormalizer},
2188 {"HistogramIntersectionKernel", SHOGUN_BASIC_CLASS __new_CHistogramIntersectionKernel},
2189 {"WaveKernel", SHOGUN_BASIC_CLASS __new_CWaveKernel},
2190 {"ConstKernel", SHOGUN_BASIC_CLASS __new_CConstKernel},
2191 {"SimpleLocalityImprovedStringKernel", SHOGUN_BASIC_CLASS __new_CSimpleLocalityImprovedStringKernel},
2192 {"PolyMatchStringKernel", SHOGUN_BASIC_CLASS __new_CPolyMatchStringKernel},
2193 {"CommUlongStringKernel", SHOGUN_BASIC_CLASS __new_CCommUlongStringKernel},
2194 {"LinearStringKernel", SHOGUN_BASIC_CLASS __new_CLinearStringKernel},
2195 {"SpectrumRBFKernel", SHOGUN_BASIC_CLASS __new_CSpectrumRBFKernel},
2196 {"WeightedCommWordStringKernel", SHOGUN_BASIC_CLASS __new_CWeightedCommWordStringKernel},
2197 {"MatchWordStringKernel", SHOGUN_BASIC_CLASS __new_CMatchWordStringKernel},
2198 {"WeightedDegreePositionStringKernel", SHOGUN_BASIC_CLASS __new_CWeightedDegreePositionStringKernel},
2199 {"SpectrumMismatchRBFKernel", SHOGUN_BASIC_CLASS __new_CSpectrumMismatchRBFKernel},
2200 {"SNPStringKernel", SHOGUN_BASIC_CLASS __new_CSNPStringKernel},
2201 {"CommWordStringKernel", SHOGUN_BASIC_CLASS __new_CCommWordStringKernel},
2202 {"SparseSpatialSampleStringKernel", SHOGUN_BASIC_CLASS __new_CSparseSpatialSampleStringKernel},
2203 {"WeightedDegreeStringKernel", SHOGUN_BASIC_CLASS __new_CWeightedDegreeStringKernel},
2204 {"LocalAlignmentStringKernel", SHOGUN_BASIC_CLASS __new_CLocalAlignmentStringKernel},
2205 {"DistantSegmentsKernel", SHOGUN_BASIC_CLASS __new_CDistantSegmentsKernel},
2206 {"PolyMatchWordStringKernel", SHOGUN_BASIC_CLASS __new_CPolyMatchWordStringKernel},
2207 {"OligoStringKernel", SHOGUN_BASIC_CLASS __new_COligoStringKernel},
2208 {"FixedDegreeStringKernel", SHOGUN_BASIC_CLASS __new_CFixedDegreeStringKernel},
2209 {"RegulatoryModulesStringKernel", SHOGUN_BASIC_CLASS __new_CRegulatoryModulesStringKernel},
2210 {"LocalityImprovedStringKernel", SHOGUN_BASIC_CLASS __new_CLocalityImprovedStringKernel},
2211 {"SubsequenceStringKernel", SHOGUN_BASIC_CLASS __new_CSubsequenceStringKernel},
2212 {"HistogramWordStringKernel", SHOGUN_BASIC_CLASS __new_CHistogramWordStringKernel},
2213 {"GaussianMatchStringKernel", SHOGUN_BASIC_CLASS __new_CGaussianMatchStringKernel},
2214 {"SalzbergWordStringKernel", SHOGUN_BASIC_CLASS __new_CSalzbergWordStringKernel},
2215 {"LinearKernel", SHOGUN_BASIC_CLASS __new_CLinearKernel},
2216 {"DistanceKernel", SHOGUN_BASIC_CLASS __new_CDistanceKernel},
2217 {"SplineKernel", SHOGUN_BASIC_CLASS __new_CSplineKernel},
2218 {"PeriodicKernel", SHOGUN_BASIC_CLASS __new_CPeriodicKernel},
2219 {"ANOVAKernel", SHOGUN_BASIC_CLASS __new_CANOVAKernel},
2220 {"AUCKernel", SHOGUN_BASIC_CLASS __new_CAUCKernel},
2221 {"TStudentKernel", SHOGUN_BASIC_CLASS __new_CTStudentKernel},
2222 {"PyramidChi2", SHOGUN_BASIC_CLASS __new_CPyramidChi2},
2223 {"CauchyKernel", SHOGUN_BASIC_CLASS __new_CCauchyKernel},
2224 {"Chi2Kernel", SHOGUN_BASIC_CLASS __new_CChi2Kernel},
2225 {"DiagKernel", SHOGUN_BASIC_CLASS __new_CDiagKernel},
2226 {"WaveletKernel", SHOGUN_BASIC_CLASS __new_CWaveletKernel},
2227 {"GaussianShiftKernel", SHOGUN_BASIC_CLASS __new_CGaussianShiftKernel},
2228 {"ProductKernel", SHOGUN_BASIC_CLASS __new_CProductKernel},
2229 {"GaussianShortRealKernel", SHOGUN_BASIC_CLASS __new_CGaussianShortRealKernel},
2230 {"GaussianKernel", SHOGUN_BASIC_CLASS __new_CGaussianKernel},
2231 {"LogKernel", SHOGUN_BASIC_CLASS __new_CLogKernel},
2232 {"CustomKernel", SHOGUN_BASIC_CLASS __new_CCustomKernel},
2233 {"InverseMultiQuadricKernel", SHOGUN_BASIC_CLASS __new_CInverseMultiQuadricKernel},
2234 {"CombinedKernel", SHOGUN_BASIC_CLASS __new_CCombinedKernel},
2235 {"PowerKernel", SHOGUN_BASIC_CLASS __new_CPowerKernel},
2236 {"BesselKernel", SHOGUN_BASIC_CLASS __new_CBesselKernel},
2237 {"ExponentialKernel", SHOGUN_BASIC_CLASS __new_CExponentialKernel},
2238 {"TensorProductPairKernel", SHOGUN_BASIC_CLASS __new_CTensorProductPairKernel},
2239 {"MMDKernelSelectionOpt", SHOGUN_BASIC_CLASS __new_CMMDKernelSelectionOpt},
2240 {"MMDKernelSelectionCombOpt", SHOGUN_BASIC_CLASS __new_CMMDKernelSelectionCombOpt},
2241 {"MMDKernelSelectionMax", SHOGUN_BASIC_CLASS __new_CMMDKernelSelectionMax},
2242 {"KernelMeanMatching", SHOGUN_BASIC_CLASS __new_CKernelMeanMatching},
2244 {"MMDKernelSelectionCombMaxL2", SHOGUN_BASIC_CLASS __new_CMMDKernelSelectionCombMaxL2},
2245 {"MMDKernelSelectionMedian", SHOGUN_BASIC_CLASS __new_CMMDKernelSelectionMedian},
2246 {"QuadraticTimeMMD", SHOGUN_BASIC_CLASS __new_CQuadraticTimeMMD},
2247 {"LinearTimeMMD", SHOGUN_BASIC_CLASS __new_CLinearTimeMMD},
2248 {"NOCCO", SHOGUN_BASIC_CLASS __new_CNOCCO},
2249 {"MeanShiftDataGenerator", SHOGUN_BASIC_CLASS __new_CMeanShiftDataGenerator},
2250 {"GaussianBlobsDataGenerator", SHOGUN_BASIC_CLASS __new_CGaussianBlobsDataGenerator},
2251 {"StreamingHashedDocDotFeatures", SHOGUN_BASIC_CLASS __new_CStreamingHashedDocDotFeatures},
2252 {"StreamingVwFeatures", SHOGUN_BASIC_CLASS __new_CStreamingVwFeatures},
2253 {"PolyFeatures", SHOGUN_BASIC_CLASS __new_CPolyFeatures},
2254 {"RealFileFeatures", SHOGUN_BASIC_CLASS __new_CRealFileFeatures},
2255 {"LBPPyrDotFeatures", SHOGUN_BASIC_CLASS __new_CLBPPyrDotFeatures},
2256 {"CombinedDotFeatures", SHOGUN_BASIC_CLASS __new_CCombinedDotFeatures},
2257 {"WDFeatures", SHOGUN_BASIC_CLASS __new_CWDFeatures},
2258 {"DataGenerator", SHOGUN_BASIC_CLASS __new_CDataGenerator},
2259 {"DummyFeatures", SHOGUN_BASIC_CLASS __new_CDummyFeatures},
2260 {"SparsePolyFeatures", SHOGUN_BASIC_CLASS __new_CSparsePolyFeatures},
2261 {"FKFeatures", SHOGUN_BASIC_CLASS __new_CFKFeatures},
2262 {"TOPFeatures", SHOGUN_BASIC_CLASS __new_CTOPFeatures},
2263 {"HashedWDFeatures", SHOGUN_BASIC_CLASS __new_CHashedWDFeatures},
2264 {"HashedDocDotFeatures", SHOGUN_BASIC_CLASS __new_CHashedDocDotFeatures},
2265 {"HashedWDFeaturesTransposed", SHOGUN_BASIC_CLASS __new_CHashedWDFeaturesTransposed},
2266 {"ExplicitSpecFeatures", SHOGUN_BASIC_CLASS __new_CExplicitSpecFeatures},
2267 {"RandomFourierDotFeatures", SHOGUN_BASIC_CLASS __new_CRandomFourierDotFeatures},
2268 {"Subset", SHOGUN_BASIC_CLASS __new_CSubset},
2269 {"LatentFeatures", SHOGUN_BASIC_CLASS __new_CLatentFeatures},
2270 {"BinnedDotFeatures", SHOGUN_BASIC_CLASS __new_CBinnedDotFeatures},
2271 {"ImplicitWeightedSpecFeatures", SHOGUN_BASIC_CLASS __new_CImplicitWeightedSpecFeatures},
2272 {"Alphabet", SHOGUN_BASIC_CLASS __new_CAlphabet},
2273 {"SNPFeatures", SHOGUN_BASIC_CLASS __new_CSNPFeatures},
2274 {"CombinedFeatures", SHOGUN_BASIC_CLASS __new_CCombinedFeatures},
2275 {"IndexFeatures", SHOGUN_BASIC_CLASS __new_CIndexFeatures},
2276 {"FactorGraphFeatures", SHOGUN_BASIC_CLASS __new_CFactorGraphFeatures},
2277 {"SubsetStack", SHOGUN_BASIC_CLASS __new_CSubsetStack},
2278 {"StreamingFileFromStringFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingFileFromStringFeatures},
2279 {"StreamingFileFromDenseFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingFileFromDenseFeatures},
2280 {"ParseBuffer", SHOGUN_TEMPLATE_CLASS __new_CParseBuffer},
2281 {"StreamingFileFromSparseFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingFileFromSparseFeatures},
2283 {"BinaryStream", SHOGUN_TEMPLATE_CLASS __new_CBinaryStream},
2284 {"MemoryMappedFile", SHOGUN_TEMPLATE_CLASS __new_CMemoryMappedFile},
2287 {"DynamicArray", SHOGUN_TEMPLATE_CLASS __new_CDynamicArray},
2288 {"TreeMachine", SHOGUN_TEMPLATE_CLASS __new_CTreeMachine},
2289 {"DecompressString", SHOGUN_TEMPLATE_CLASS __new_CDecompressString},
2290 {"StreamingDenseFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingDenseFeatures},
2291 {"StreamingHashedDenseFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingHashedDenseFeatures},
2292 {"StreamingHashedSparseFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingHashedSparseFeatures},
2293 {"StreamingStringFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingStringFeatures},
2294 {"StreamingSparseFeatures", SHOGUN_TEMPLATE_CLASS __new_CStreamingSparseFeatures},
2295 {"SparseFeatures", SHOGUN_TEMPLATE_CLASS __new_CSparseFeatures},
2296 {"DenseSubSamplesFeatures", SHOGUN_TEMPLATE_CLASS __new_CDenseSubSamplesFeatures},
2297 {"DenseFeatures", SHOGUN_TEMPLATE_CLASS __new_CDenseFeatures},
2298 {"StringFileFeatures", SHOGUN_TEMPLATE_CLASS __new_CStringFileFeatures},
2299 {"HashedSparseFeatures", SHOGUN_TEMPLATE_CLASS __new_CHashedSparseFeatures},
2300 {"HashedDenseFeatures", SHOGUN_TEMPLATE_CLASS __new_CHashedDenseFeatures},
2301 {"StringFeatures", SHOGUN_TEMPLATE_CLASS __new_CStringFeatures},
2302 {"MatrixFeatures", SHOGUN_TEMPLATE_CLASS __new_CMatrixFeatures},
2303 {"DenseSubsetFeatures", SHOGUN_TEMPLATE_CLASS __new_CDenseSubsetFeatures},
2304 {"StoreScalarAggregator", SHOGUN_TEMPLATE_CLASS __new_CStoreScalarAggregator},
2305 {"VectorResult", SHOGUN_TEMPLATE_CLASS __new_CVectorResult},
2306 {"ScalarResult", SHOGUN_TEMPLATE_CLASS __new_CScalarResult},
2307 {"SparseMatrixOperator", SHOGUN_TEMPLATE_CLASS __new_CSparseMatrixOperator},
2308 {"DenseMatrixOperator", SHOGUN_TEMPLATE_CLASS __new_CDenseMatrixOperator}, {NULL, NULL}
2309 };
2310 
2311 CSGObject* shogun::new_sgserializable(const char* sgserializable_name,
2312  EPrimitiveType generic)
2313 {
2314  for (class_list_entry_t* i=class_list; i->m_class_name != NULL;
2315  i++)
2316  {
2317  if (strncmp(i->m_class_name, sgserializable_name, STRING_LEN) == 0)
2318  return i->m_new_sgserializable(generic);
2319  }
2320 
2321  return NULL;
2322 }
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwParser(EPrimitiveType g)
Definition: class_list.cpp:609
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingAsciiFile(EPrimitiveType g)
Definition: class_list.cpp:624
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CTreeMachine(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CCompressor(EPrimitiveType g)
Definition: class_list.cpp:637
static SHOGUN_BASIC_CLASS CSGObject * __new_CMMDKernelSelectionMedian(EPrimitiveType g)
An I/O buffer class.
Definition: IOBuffer.h:41
static SHOGUN_BASIC_CLASS CSGObject * __new_CQDA(EPrimitiveType g)
Definition: class_list.cpp:699
Class Time that implements a stopwatch based on either cpu time or wall clock time.
Definition: Time.h:47
static SHOGUN_BASIC_CLASS CSGObject * __new_CBaseMulticlassMachine(EPrimitiveType g)
Definition: class_list.cpp:776
Base class that stores the result of an independent job when the result is a scalar.
Definition: ScalarResult.h:24
static SHOGUN_BASIC_CLASS CSGObject * __new_CWDSVMOcas(EPrimitiveType g)
Definition: class_list.cpp:589
static SHOGUN_BASIC_CLASS CSGObject * __new_CHashedWDFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingHashedDocDotFeatures(EPrimitiveType g)
class Task used to represent tasks in multitask learning. Essentially it represent a set of feature v...
Definition: Task.h:27
class CosineDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CKLCholeskyInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:759
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskKernelPlifNormalizer(EPrimitiveType g)
Definition: class_list.cpp:794
static SHOGUN_BASIC_CLASS CSGObject * __new_CCosineDistance(EPrimitiveType g)
Definition: class_list.cpp:734
static SHOGUN_BASIC_CLASS CSGObject * __new_COnlineSVMSGD(EPrimitiveType g)
Definition: class_list.cpp:586
class SVMLin
Definition: SVMLin.h:22
static SHOGUN_BASIC_CLASS CSGObject * __new_CBallTree(EPrimitiveType g)
Definition: class_list.cpp:713
Wrapper class for an index subset which is used by SubsetStack.
Definition: Subset.h:24
UI labels.
Definition: GUILabels.h:24
static SHOGUN_BASIC_CLASS CSGObject * __new_CMeanAbsoluteError(EPrimitiveType g)
Definition: class_list.cpp:874
class HammingWordDistance
the class DimensionReductionPreprocessor, a base class for preprocessors used to lower the dimensiona...
class LinearLocalTangentSpaceAlignment converter used to construct embeddings as described in: ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CJediDiag(EPrimitiveType g)
Definition: class_list.cpp:827
Class CFactorType defines the way of factor parameterization.
Definition: FactorType.h:24
Class that models Soft-Max likelihood.
static SHOGUN_BASIC_CLASS CSGObject * __new_CFile(EPrimitiveType g)
Definition: class_list.cpp:629
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossValidationPrintOutput(EPrimitiveType g)
Definition: class_list.cpp:870
Spherical kernel.
A Restricted Boltzmann Machine.
Definition: RBM.h:123
Positional PWM.
Definition: PositionalPWM.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CKLDualInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:755
static SHOGUN_BASIC_CLASS CSGObject * __new_CDirectLinearSolverComplex(EPrimitiveType g)
Definition: class_list.cpp:836
The MultitaskKernel allows Multitask Learning via a modified kernel function.
Class KernelRidgeRegression implements Kernel Ridge Regression - a regularized least square method fo...
static SHOGUN_BASIC_CLASS CSGObject * __new_CIndexBlockGroup(EPrimitiveType g)
Definition: class_list.cpp:638
static SHOGUN_BASIC_CLASS CSGObject * __new_CLocalityPreservingProjections(EPrimitiveType g)
Definition: class_list.cpp:667
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CMatrixFeatures(EPrimitiveType g)
Computes the standard linear kernel on CDotFeatures.
Definition: LinearKernel.h:35
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CScalarResult(EPrimitiveType g)
base class for cross-validation evaluation. Given a learning machine, a splitting strategy...
static SHOGUN_BASIC_CLASS CSGObject * __new_CSerializableAsciiFile(EPrimitiveType g)
Definition: class_list.cpp:630
static SHOGUN_BASIC_CLASS CSGObject * __new_CJediSep(EPrimitiveType g)
Definition: class_list.cpp:657
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskLogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:798
Class OnlineLinearMachine is a generic interface for linear machines like classifiers which work thro...
Class that models Logit likelihood.
static SHOGUN_BASIC_CLASS CSGObject * __new_CProtobufFile(EPrimitiveType g)
Definition: class_list.cpp:619
Class QDA implements Quadratic Discriminant Analysis.
Definition: QDA.h:36
Base class of the labels used in Structured Output (SO) problems.
The standard Sigmoid kernel computed on dense real valued features.
Definition: SigmoidKernel.h:31
The class CNGramTokenizer is used to tokenize a SGVector into n-grams.
Latent Features class The class if for representing features for latent learning, e...
The class MulticlassOVREvaluation used to compute evaluation parameters of multiclass classification ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CCombinedDotFeatures(EPrimitiveType g)
CAbsoluteDeviationLoss implements the absolute deviation loss function. .
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogitVGLikelihood(EPrimitiveType g)
Definition: class_list.cpp:764
The class ContingencyTableEvaluation a base class used to evaluate 2-class classification with TP...
Class CVwNativeCacheReader reads from a cache exactly as that which has been produced by VW's default...
static SHOGUN_BASIC_CLASS CSGObject * __new_CLocalAlignmentStringKernel(EPrimitiveType g)
Definition: class_list.cpp:972
Computes the standard polynomial kernel on CDotFeatures.
Definition: PolyKernel.h:38
static SHOGUN_BASIC_CLASS CSGObject * __new_CLOOCrossValidationSplitting(EPrimitiveType g)
Definition: class_list.cpp:896
This class implements streaming features for a document collection. Like in the standard Bag-of-Words...
Model selection class which searches for the best model by a gradient-search.
The Gaussian exact form inference method class.
static SHOGUN_BASIC_CLASS CSGObject * __new_CUWedgeSep(EPrimitiveType g)
Definition: class_list.cpp:658
Class StreamingAsciiFile to read vector-by-vector from ASCII files.
Class that models Gaussian likelihood.
static SHOGUN_BASIC_CLASS CSGObject * __new_CTwoStateModel(EPrimitiveType g)
Definition: class_list.cpp:548
static SHOGUN_BASIC_CLASS CSGObject * __new_CMMDKernelSelectionCombMaxL2(EPrimitiveType g)
The Laplace approximation FITC inference method with LBFGS class for regression and binary classifica...
static SHOGUN_BASIC_CLASS CSGObject * __new_CLocalityImprovedStringKernel(EPrimitiveType g)
Definition: class_list.cpp:978
Real Labels are real-valued labels.
static SHOGUN_BASIC_CLASS CSGObject * __new_CProbitVGLikelihood(EPrimitiveType g)
Definition: class_list.cpp:753
MKLMulticlass is a class for L1-norm Multiclass MKL.
Definition: MKLMulticlass.h:40
static SHOGUN_BASIC_CLASS CSGObject * __new_CStructuredAccuracy(EPrimitiveType g)
Definition: class_list.cpp:883
a string class embedding a string in a compact bit representation
Definition: BitString.h:30
static SHOGUN_BASIC_CLASS CSGObject * __new_CRealFileFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelDensity(EPrimitiveType g)
Definition: class_list.cpp:821
class GMNPLib Library of solvers for Generalized Minimal Norm Problem (GMNP).
Definition: GMNPLib.h:64
UI kernel.
Definition: GUIKernel.h:24
class IndexBlockGroup used to represent group-based feature relation.
static SHOGUN_BASIC_CLASS CSGObject * __new_CPyramidChi2(EPrimitiveType g)
Definition: class_list.cpp:990
Class that generates jobs for computing logarithm of a dense matrix linear operator.
static SHOGUN_BASIC_CLASS CSGObject * __new_CCombinedKernel(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CConstMean(EPrimitiveType g)
Definition: class_list.cpp:774
static SHOGUN_BASIC_CLASS CSGObject * __new_CCanberraMetric(EPrimitiveType g)
Definition: class_list.cpp:740
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CDenseFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CPositionalPWM(EPrimitiveType g)
Definition: class_list.cpp:819
The Factor Analysis class is used to embed data using Factor Analysis algorithm.
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandom(EPrimitiveType g)
Definition: class_list.cpp:832
static SHOGUN_BASIC_CLASS CSGObject * __new_CLineReader(EPrimitiveType g)
Definition: class_list.cpp:627
static SHOGUN_BASIC_CLASS CSGObject * __new_CSortUlongString(EPrimitiveType g)
Definition: class_list.cpp:918
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCRandomDenseEncoder(EPrimitiveType g)
Definition: class_list.cpp:684
Neural layer with leaky rectified linear neurons.
The Diagonal Kernel returns a constant for the diagonal and zero otherwise.
Definition: DiagKernel.h:28
static SHOGUN_BASIC_CLASS CSGObject * __new_CLeastAngleRegression(EPrimitiveType g)
Definition: class_list.cpp:581
threshold based rejection strategy
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassLogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:696
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearStringKernel(EPrimitiveType g)
Definition: class_list.cpp:962
class to implement LibLinear
Definition: LibLinearMTL.h:91
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogDetEstimator(EPrimitiveType g)
Definition: class_list.cpp:841
class PrecisionMeasure used to measure precision of 2-class classifier.
class WDSVMOcas
Definition: WDSVMOcas.h:28
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultiquadricKernel(EPrimitiveType g)
Definition: class_list.cpp:941
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralLayers(EPrimitiveType g)
Definition: class_list.cpp:857
static SHOGUN_BASIC_CLASS CSGObject * __new_CBinnedDotFeatures(EPrimitiveType g)
Class GaussianProcessRegression implements regression based on Gaussian Processes.
Gaussian Kernel with Automatic Relevance Detection with supporting Sparse inference.
experimental abstract native multiclass machine class
class SparseEucldeanDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CFFDiag(EPrimitiveType g)
Definition: class_list.cpp:829
static SHOGUN_BASIC_CLASS CSGObject * __new_CTaskTree(EPrimitiveType g)
Definition: class_list.cpp:792
static SHOGUN_BASIC_CLASS CSGObject * __new_CStructuredData(EPrimitiveType g)
Definition: class_list.cpp:643
Class DualLibQPBMSOSVM that uses Bundle Methods for Regularized Risk Minimization algorithms for stru...
static SHOGUN_BASIC_CLASS CSGObject * __new_CJacobiEllipticFunctions(EPrimitiveType g)
Definition: class_list.cpp:834
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorGraphObservation(EPrimitiveType g)
Definition: class_list.cpp:904
CExponentialLoss implements the exponential loss function. .
Class CStreamingFileFromDenseFeatures is a derived class of CStreamingFile which creates an input sou...
Implementation of circular buffer This buffer has logical structure such as queue (FIFO)...
This class implements streaming features with dense feature vectors.
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralConvolutionalLayer(EPrimitiveType g)
Definition: class_list.cpp:853
static SHOGUN_BASIC_CLASS CSGObject * __new_CDixonQTestRejectionStrategy(EPrimitiveType g)
Definition: class_list.cpp:715
This class offers access to the Oligo Kernel introduced by Meinicke et al. in 2004.
static SHOGUN_BASIC_CLASS CSGObject * __new_CQDiag(EPrimitiveType g)
Definition: class_list.cpp:825
static SHOGUN_BASIC_CLASS CSGObject * __new_CWaveKernel(EPrimitiveType g)
Definition: class_list.cpp:957
multiclass one vs one strategy used to train generic multiclass machines for K-class problems with bu...
static SHOGUN_BASIC_CLASS CSGObject * __new_CCommWordStringKernel(EPrimitiveType g)
Definition: class_list.cpp:969
CTaxonomy is used to describe hierarchical structure between tasks.
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorGraphDataGenerator(EPrimitiveType g)
Definition: class_list.cpp:566
static SHOGUN_BASIC_CLASS CSGObject * __new_CKNN(EPrimitiveType g)
Definition: class_list.cpp:718
static SHOGUN_BASIC_CLASS CSGObject * __new_CMahalanobisDistance(EPrimitiveType g)
Definition: class_list.cpp:735
The CommUlongString kernel may be used to compute the spectrum kernel from strings that have been map...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingStringFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CCARTree(EPrimitiveType g)
Definition: class_list.cpp:707
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingHashedDenseFeatures(EPrimitiveType g)
DiceKernelNormalizer performs kernel normalization inspired by the Dice coefficient (see http://en...
The MultitaskKernel allows Multitask Learning via a modified kernel function.
The class is used to serialize and deserialize variables for the optimization framework.
static SHOGUN_BASIC_CLASS CSGObject * __new_CSimpleLocalityImprovedStringKernel(EPrimitiveType g)
Definition: class_list.cpp:959
#define SHOGUN_BASIC_CLASS
Definition: class_list.cpp:536
Class CMultilabelSOLabels used in the application of Structured Output (SO) learning to Multilabel Cl...
LibSVM.
Definition: LibSVM.h:30
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskLinearMachine(EPrimitiveType g)
Definition: class_list.cpp:800
static SHOGUN_BASIC_CLASS CSGObject * __new_CParameterCombination(EPrimitiveType g)
Definition: class_list.cpp:677
static SHOGUN_BASIC_CLASS CSGObject * __new_CEMMixtureModel(EPrimitiveType g)
Definition: class_list.cpp:823
static SHOGUN_BASIC_CLASS CSGObject * __new_CBrayCurtisDistance(EPrimitiveType g)
Definition: class_list.cpp:730
Template class SimpleFile to read and write from files.
Definition: SimpleFile.h:30
A base class for Gaussian Processes.
CSGObject *(* new_sgserializable_t)(EPrimitiveType generic)
class IndexBlockTree used to represent tree guided feature relation.
static SHOGUN_BASIC_CLASS CSGObject * __new_CRegulatoryModulesStringKernel(EPrimitiveType g)
Definition: class_list.cpp:977
The Custom Kernel allows for custom user provided kernel matrices.
Definition: CustomKernel.h:36
static SHOGUN_BASIC_CLASS CSGObject * __new_CNGramTokenizer(EPrimitiveType g)
Definition: class_list.cpp:649
This class implements the NOrmalized Cross Covariance Operator (NOCCO) based independence test as des...
Definition: NOCCO.h:109
The Product kernel is used to combine a number of kernels into a single ProductKernel object by eleme...
Definition: ProductKernel.h:41
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassOVREvaluation(EPrimitiveType g)
Definition: class_list.cpp:875
class JediSep
Definition: JediSep.h:35
The class IndexFeatures implements features that contain the index of the features. This features used in the CCustomKernel::init to make the subset of the kernel matrix. Initial CIndexFeature of row_idx and col_idx, pass them to the CCustomKernel::init(row_idx, col_idx), then use CCustomKernel::get_kernel_matrix() will get the sub kernel matrix specified by the row_idx and col_idx.
Definition: IndexFeatures.h:53
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorGraphLabels(EPrimitiveType g)
Definition: class_list.cpp:905
static SHOGUN_BASIC_CLASS CSGObject * __new_CBinaryFile(EPrimitiveType g)
Definition: class_list.cpp:625
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorType(EPrimitiveType g)
Definition: class_list.cpp:541
static SHOGUN_BASIC_CLASS CSGObject * __new_CPlifArray(EPrimitiveType g)
Definition: class_list.cpp:545
Class that computes multiple independent instances of computation jobs sequentially.
Class CVwEnvironment is the environment used by VW.
Definition: VwEnvironment.h:41
static SHOGUN_BASIC_CLASS CSGObject * __new_CGraphCut(EPrimitiveType g)
Definition: class_list.cpp:539
Represents a single layer neural autoencoder.
Definition: Autoencoder.h:86
Class GaussianProcessClassification implements binary and multiclass classification based on Gaussian...
class CTDistributedStochasticNeighborEmbedding used to embed data using t-distributed stochastic neig...
class to perform Least Squares Regression
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CDynamicArray(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CAlphabet(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeighborhoodPreservingEmbedding(EPrimitiveType g)
Definition: class_list.cpp:654
static SHOGUN_BASIC_CLASS CSGObject * __new_CCustomKernel(EPrimitiveType g)
Class CFWSOSVM solves SOSVM using Frank-Wolfe algorithm [1].
Definition: FWSOSVM.h:26
simplified version of Dixon's Q test outlier based rejection strategy. Statistic values are taken fro...
Implementaion of rational approximation of a operator-function times vector where the operator functi...
static SHOGUN_BASIC_CLASS CSGObject * __new_CStructuredLabels(EPrimitiveType g)
Definition: class_list.cpp:910
Class MCLDA implements multiclass Linear Discriminant Analysis.
Definition: MCLDA.h:39
Class that represents the job of applying the log of a CDenseMatrixOperator on a real vector...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassSVM(EPrimitiveType g)
Definition: class_list.cpp:700
class that uses conjugate gradient method of solving a linear system involving a real valued linear o...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CHashedDenseFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CBinaryLabels(EPrimitiveType g)
Definition: class_list.cpp:911
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianNaiveBayes(EPrimitiveType g)
Definition: class_list.cpp:720
static SHOGUN_BASIC_CLASS CSGObject * __new_CDirectSparseLinearSolver(EPrimitiveType g)
Definition: class_list.cpp:838
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassLabels(EPrimitiveType g)
Definition: class_list.cpp:912
The Jensen-Shannon kernel operating on real-valued vectors computes the Jensen-Shannon distance betwe...
UI HMM (Hidden Markov Model)
Definition: GUIHMM.h:26
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandomSearchModelSelection(EPrimitiveType g)
Definition: class_list.cpp:675
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralNetworkFileReader(EPrimitiveType g)
Definition: class_list.cpp:626
static SHOGUN_BASIC_CLASS CSGObject * __new_CSingleLaplacianInferenceMethodWithLBFGS(EPrimitiveType g)
Definition: class_list.cpp:756
class GNPPLib, a Library of solvers for Generalized Nearest Point Problem (GNPP). ...
Definition: GNPPLib.h:30
class CrossCorrelationMeasure used to measure cross correlation coefficient of 2-class classifier...
static SHOGUN_BASIC_CLASS CSGObject * __new_CExplicitSpecFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIPreprocessor(EPrimitiveType g)
Definition: class_list.cpp:805
The class GaussianMatchStringKernel computes a variant of the Gaussian kernel on strings of same leng...
static SHOGUN_BASIC_CLASS CSGObject * __new_CCircularBuffer(EPrimitiveType g)
Definition: class_list.cpp:646
class Latent Structured Output SVM, an structured output based machine for classification problems wi...
Definition: LatentSOSVM.h:25
Implements optimal kernel selection for single kernels. Given a number of baseline kernels...
Class FFDiag.
Definition: FFDiag.h:35
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStoreScalarAggregator(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearTimeMMD(EPrimitiveType g)
This class implements Ball tree. The ball tree is contructed using the top-down approach. cf. ftp://ftp.icsi.berkeley.edu/pub/techreports/1989/tr-89-063.pdf.
Definition: BallTree.h:45
static SHOGUN_BASIC_CLASS CSGObject * __new_CZeroMeanCenterKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:948
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogitDVGLikelihood(EPrimitiveType g)
Definition: class_list.cpp:769
class MinkowskiMetric
CVwParser is the object which provides the functions to parse examples from buffered input...
Definition: VwParser.h:48
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIStructure(EPrimitiveType g)
Definition: class_list.cpp:810
static SHOGUN_BASIC_CLASS CSGObject * __new_CSVMLin(EPrimitiveType g)
Definition: class_list.cpp:587
static SHOGUN_BASIC_CLASS CSGObject * __new_CTensorProductPairKernel(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLDA(EPrimitiveType g)
Definition: class_list.cpp:599
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibLinearRegression(EPrimitiveType g)
Definition: class_list.cpp:576
This class implements the CHAID algorithm proposed by Kass (1980) for decision tree learning...
Definition: CHAIDTree.h:90
static SHOGUN_BASIC_CLASS CSGObject * __new_CFisherLDA(EPrimitiveType g)
Definition: class_list.cpp:914
Class CHMSVMModel that represents the application specific model and contains the application depende...
Definition: HMSVMModel.h:31
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearMulticlassMachine(EPrimitiveType g)
Definition: class_list.cpp:779
class AccuracyMeasure used to measure accuracy of 2-class classifier.
Gaussian distribution interface.
Definition: Gaussian.h:50
static SHOGUN_BASIC_CLASS CSGObject * __new_CGradientCriterion(EPrimitiveType g)
Definition: class_list.cpp:866
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIConverter(EPrimitiveType g)
Definition: class_list.cpp:809
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingFile(EPrimitiveType g)
Definition: class_list.cpp:620
static SHOGUN_BASIC_CLASS CSGObject * __new_CJensenShannonKernel(EPrimitiveType g)
Definition: class_list.cpp:945
class MPDSVM
Definition: MPDSVM.h:24
static SHOGUN_BASIC_CLASS CSGObject * __new_CLocalTangentSpaceAlignment(EPrimitiveType g)
Definition: class_list.cpp:674
class CTwoStateModel class for the internal two-state representation used in the CHMSVMModel.
Definition: TwoStateModel.h:26
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralNetwork(EPrimitiveType g)
Definition: class_list.cpp:855
static SHOGUN_BASIC_CLASS CSGObject * __new_CDenseExactLogJob(EPrimitiveType g)
Definition: class_list.cpp:842
Template class SparseFeatures implements sparse matrices.
Preprocessor FisherLDA attempts to model the difference between the classes of data by performing lin...
Definition: FisherLDA.h:92
static SHOGUN_BASIC_CLASS CSGObject * __new_CDiffusionMaps(EPrimitiveType g)
Definition: class_list.cpp:653
Base class that stores the result of an independent job.
Definition: JobResult.h:21
static SHOGUN_BASIC_CLASS CSGObject * __new_CInverseMultiQuadricKernel(EPrimitiveType g)
spectrum rbf kernel
static SHOGUN_BASIC_CLASS CSGObject * __new_CJADiag(EPrimitiveType g)
Definition: class_list.cpp:828
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIDistance(EPrimitiveType g)
Definition: class_list.cpp:807
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralLinearLayer(EPrimitiveType g)
Definition: class_list.cpp:852
static SHOGUN_BASIC_CLASS CSGObject * __new_CSNPStringKernel(EPrimitiveType g)
Definition: class_list.cpp:968
class Jade
Definition: Jade.h:37
static SHOGUN_BASIC_CLASS CSGObject * __new_CNOCCO(EPrimitiveType g)
class Multitask Least Squares Regression, a machine to solve regression problems with a few tasks rel...
static SHOGUN_BASIC_CLASS CSGObject * __new_CSmoothHingeLoss(EPrimitiveType g)
Definition: class_list.cpp:931
static SHOGUN_BASIC_CLASS CSGObject * __new_CDiagKernel(EPrimitiveType g)
Definition: class_list.cpp:993
The FixedDegree String kernel takes as input two strings of same size and counts the number of matche...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultidimensionalScaling(EPrimitiveType g)
Definition: class_list.cpp:662
Class that models Logit likelihood and uses variational piecewise bound to approximate the following ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussian(EPrimitiveType g)
Definition: class_list.cpp:816
class StochasticProximityEmbedding used to construct embeddings of data using the Stochastic Proximit...
Class JADiagOrth.
Definition: JADiagOrth.h:35
A generic multi-layer neural network.
Class QDiag.
Definition: QDiag.h:34
static SHOGUN_BASIC_CLASS CSGObject * __new_CNativeMulticlassMachine(EPrimitiveType g)
Definition: class_list.cpp:749
The periodic kernel as described in The Kernel Cookbook by David Duvenaud: http://people.seas.harvard.edu/~dduvenaud/cookbook/.
static SHOGUN_BASIC_CLASS CSGObject * __new_CLMNN(EPrimitiveType g)
Definition: class_list.cpp:902
static SHOGUN_BASIC_CLASS CSGObject * __new_CRationalQuadraticKernel(EPrimitiveType g)
Definition: class_list.cpp:944
UI time.
Definition: GUITime.h:23
class FeatureBlockLogisticRegression, a linear binary logistic loss classifier for problems with comp...
The class Alphabet implements an alphabet and alphabet utility functions.
Definition: Alphabet.h:91
Class Averaged Perceptron implements the standard linear (online) algorithm. Averaged perceptron is t...
This class is identical to the CDenseFeatures class except that it hashes each dimension to a new fea...
static SHOGUN_BASIC_CLASS CSGObject * __new_CRescaleFeatures(EPrimitiveType g)
Definition: class_list.cpp:920
static SHOGUN_BASIC_CLASS CSGObject * __new_CBitString(EPrimitiveType g)
Definition: class_list.cpp:639
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearStructuredOutputMachine(EPrimitiveType g)
Definition: class_list.cpp:746
This class acts as an alternative to the CStreamingSparseFeatures class and their difference is that ...
ANOVA (ANalysis Of VAriances) kernel.
Definition: ANOVAKernel.h:37
static SHOGUN_BASIC_CLASS CSGObject * __new_CPolyKernel(EPrimitiveType g)
Definition: class_list.cpp:942
The class MulticlassAccuracy used to compute accuracy of multiclass classification.
static SHOGUN_BASIC_CLASS CSGObject * __new_CSignal(EPrimitiveType g)
Definition: class_list.cpp:644
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossValidationSplitting(EPrimitiveType g)
Definition: class_list.cpp:876
class Tanimoto coefficient
static SHOGUN_BASIC_CLASS CSGObject * __new_CDeepAutoencoder(EPrimitiveType g)
Definition: class_list.cpp:854
static SHOGUN_BASIC_CLASS CSGObject * __new_CScatterSVM(EPrimitiveType g)
Definition: class_list.cpp:717
class ManhattanMetric
Compression library for compressing and decompressing buffers using one of the standard compression a...
Definition: Compressor.h:46
static SHOGUN_BASIC_CLASS CSGObject * __new_CDenseMatrixExactLog(EPrimitiveType g)
Definition: class_list.cpp:846
static SHOGUN_BASIC_CLASS CSGObject * __new_CGMNPSVM(EPrimitiveType g)
Definition: class_list.cpp:698
static SHOGUN_BASIC_CLASS CSGObject * __new_CSingleFITCLaplacianInferenceMethodWithLBFGS(EPrimitiveType g)
Definition: class_list.cpp:758
static SHOGUN_BASIC_CLASS CSGObject * __new_CCHAIDTree(EPrimitiveType g)
Definition: class_list.cpp:708
static SHOGUN_BASIC_CLASS CSGObject * __new_CWeightedDegreePositionStringKernel(EPrimitiveType g)
Definition: class_list.cpp:966
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCHDDecoder(EPrimitiveType g)
Definition: class_list.cpp:690
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassLibLinear(EPrimitiveType g)
Definition: class_list.cpp:702
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandomFourierGaussPreproc(EPrimitiveType g)
Definition: class_list.cpp:925
static SHOGUN_BASIC_CLASS CSGObject * __new_CLMNNStatistics(EPrimitiveType g)
Definition: class_list.cpp:903
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskROCEvaluation(EPrimitiveType g)
Definition: class_list.cpp:799
class MultitaskClusteredLogisticRegression, a classifier for multitask problems. Supports only task g...
class ChiSquareDistance
The SingleFITCLaplace approximation inference method class for regression and binary Classification...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassOCAS(EPrimitiveType g)
Definition: class_list.cpp:701
static SHOGUN_BASIC_CLASS CSGObject * __new_CCommUlongStringKernel(EPrimitiveType g)
Definition: class_list.cpp:961
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIFeatures(EPrimitiveType g)
Definition: class_list.cpp:803
static SHOGUN_BASIC_CLASS CSGObject * __new_COnlineLibLinear(EPrimitiveType g)
Definition: class_list.cpp:582
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingFileFromStringFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CDualLibQPBMSOSVM(EPrimitiveType g)
Definition: class_list.cpp:555
VwAdaptiveLearner uses an adaptive subgradient technique to update weights.
static SHOGUN_BASIC_CLASS CSGObject * __new_CCustomDistance(EPrimitiveType g)
Definition: class_list.cpp:729
Generalized T-Student kernel.
class LocalTangentSpaceAlignment used to embed data using Local Tangent Space Alignment (LTSA) algori...
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorGraph(EPrimitiveType g)
Definition: class_list.cpp:565
static SHOGUN_BASIC_CLASS CSGObject * __new_CHomogeneousKernelMap(EPrimitiveType g)
Definition: class_list.cpp:916
static SHOGUN_BASIC_CLASS CSGObject * __new_CContingencyTableEvaluation(EPrimitiveType g)
Definition: class_list.cpp:885
class IntronList
Definition: SegmentLoss.h:24
Class LMNNStatistics used to give access to intermediate results obtained training LMNN...
Definition: LMNN.h:250
Preprocessor SortUlongString, sorts the indivual strings in ascending order.
The SalzbergWordString kernel implements the Salzberg kernel.
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossValidationMKLStorage(EPrimitiveType g)
Definition: class_list.cpp:871
static SHOGUN_BASIC_CLASS CSGObject * __new_CLeastSquaresRegression(EPrimitiveType g)
Definition: class_list.cpp:579
static SHOGUN_BASIC_CLASS CSGObject * __new_CWeightedDegreeStringKernel(EPrimitiveType g)
Definition: class_list.cpp:971
static SHOGUN_BASIC_CLASS CSGObject * __new_CManifoldSculpting(EPrimitiveType g)
Definition: class_list.cpp:666
static SHOGUN_BASIC_CLASS CSGObject * __new_CPCA(EPrimitiveType g)
Definition: class_list.cpp:913
Preprocessor LogPlusOne does what the name says, it adds one to a dense real valued vector and takes ...
Definition: LogPlusOne.h:34
Implementation of optimal kernel selection for combined kernel. This class selects a combination of b...
A generic KernelMachine interface.
Definition: KernelMachine.h:51
static SHOGUN_BASIC_CLASS CSGObject * __new_CGEMPLP(EPrimitiveType g)
Definition: class_list.cpp:558
Multiple Kernel Learning for one-class-classification.
Definition: MKLOneClass.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CExactInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:771
class TaskGroup used to represent a group of tasks. Tasks in group do not overlap.
Definition: TaskGroup.h:28
static SHOGUN_BASIC_CLASS CSGObject * __new_CMachine(EPrimitiveType g)
Definition: class_list.cpp:744
static SHOGUN_BASIC_CLASS CSGObject * __new_CNormalSampler(EPrimitiveType g)
Definition: class_list.cpp:839
Class for buffered reading from a ascii file.
Definition: LineReader.h:24
Agglomerative hierarchical single linkage clustering.
Definition: Hierarchical.h:38
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossValidation(EPrimitiveType g)
Definition: class_list.cpp:879
Class CSequenceLabels used e.g. in the application of Structured Output (SO) learning to Hidden Marko...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingHashedSparseFeatures(EPrimitiveType g)
class KernelLocallyLinearEmbedding used to construct embeddings of data using kernel formulation of L...
static SHOGUN_BASIC_CLASS CSGObject * __new_CNearestCentroid(EPrimitiveType g)
Definition: class_list.cpp:600
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibLinearMTL(EPrimitiveType g)
Definition: class_list.cpp:784
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CDenseSubsetFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CSOBI(EPrimitiveType g)
Definition: class_list.cpp:656
static SHOGUN_BASIC_CLASS CSGObject * __new_CChiSquareDistance(EPrimitiveType g)
Definition: class_list.cpp:724
static SHOGUN_BASIC_CLASS CSGObject * __new_CKMeans(EPrimitiveType g)
Definition: class_list.cpp:899
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingFileFromDenseFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CSparsePolyFeatures(EPrimitiveType g)
The class SNPStringKernel computes a variant of the polynomial kernel on strings of same length...
static SHOGUN_BASIC_CLASS CSGObject * __new_CStochasticProximityEmbedding(EPrimitiveType g)
Definition: class_list.cpp:655
Features that compute the Weighted Degreee Kernel feature space explicitly.
Definition: WDFeatures.h:30
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCForestEncoder(EPrimitiveType g)
Definition: class_list.cpp:683
static SHOGUN_BASIC_CLASS CSGObject * __new_CExponentialKernel(EPrimitiveType g)
type to encapsulate the results of an evaluation run. May contain confidence interval (if conf_int_al...
static SHOGUN_BASIC_CLASS CSGObject * __new_CDynamicObjectArray(EPrimitiveType g)
Definition: class_list.cpp:652
The Kernel distance takes a distance as input.
The Exponential Kernel, closely related to the Gaussian Kernel computed on CDotFeatures.
TanimotoKernelNormalizer performs kernel normalization inspired by the Tanimoto coefficient (see http...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CSimpleFile(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLatentSVM(EPrimitiveType g)
Definition: class_list.cpp:901
Class to create unbiased estimators of . For each estimate, it samples trace vectors (one by one) and...
class ManhattanWordDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CAUCKernel(EPrimitiveType g)
Definition: class_list.cpp:988
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearKernel(EPrimitiveType g)
Definition: class_list.cpp:983
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelMachine(EPrimitiveType g)
Definition: class_list.cpp:780
Base class for neural network layers.
Definition: NeuralLayer.h:87
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogKernel(EPrimitiveType g)
Definition: class_list.cpp:999
Class FactorGraphLabels used e.g. in the application of Structured Output (SO) learning with the Fact...
Computes the Spline Kernel function which is the cubic polynomial.
Definition: SplineKernel.h:38
static SHOGUN_BASIC_CLASS CSGObject * __new_CTanimotoKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:955
class DomainAdaptationSVMLinear
Class CMultilabelModel represents application specific model and contains application dependent logic...
Model selection class which searches for the best model by a grid- search. See CModelSelection for de...
class Tron
Definition: tron.h:55
This class implements the kernel density estimation technique. Kernel density estimation is a non-par...
Definition: KernelDensity.h:61
class LibSVMMultiClass. Does one vs one classification.
static SHOGUN_BASIC_CLASS CSGObject * __new_CDisjointSet(EPrimitiveType g)
Definition: class_list.cpp:561
static SHOGUN_BASIC_CLASS CSGObject * __new_CStochasticSOSVM(EPrimitiveType g)
Definition: class_list.cpp:550
This is the implementation of EM specialized for Mixture models.
static SHOGUN_BASIC_CLASS CSGObject * __new_CSquaredLoss(EPrimitiveType g)
Definition: class_list.cpp:933
static SHOGUN_BASIC_CLASS CSGObject * __new_CSVMSGD(EPrimitiveType g)
Definition: class_list.cpp:592
The WeightedCommWordString kernel may be used to compute the weighted spectrum kernel (i...
static SHOGUN_BASIC_CLASS CSGObject * __new_CHistogramIntersectionKernel(EPrimitiveType g)
Definition: class_list.cpp:956
static SHOGUN_BASIC_CLASS CSGObject * __new_CFastICA(EPrimitiveType g)
Definition: class_list.cpp:661
Multiple Kernel Learning for regression.
Definition: MKLRegression.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianMatchStringKernel(EPrimitiveType g)
Definition: class_list.cpp:981
Class CMeanSquaredLogError used to compute an error of regression model.
static SHOGUN_BASIC_CLASS CSGObject * __new_CCCSOSVM(EPrimitiveType g)
Definition: class_list.cpp:564
static SHOGUN_BASIC_CLASS CSGObject * __new_CBALMeasure(EPrimitiveType g)
Definition: class_list.cpp:888
Class LDA implements regularized Linear Discriminant Analysis.
Definition: LDA.h:90
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibLinear(EPrimitiveType g)
Definition: class_list.cpp:594
Computes the Tensor Product Pair Kernel (TPPK).
class Plif
Definition: Plif.h:40
class Multitask Logistic Regression used to solve classification problems with a few tasks related vi...
A generic DistanceMachine interface.
A generic learning machine interface.
Definition: Machine.h:143
static SHOGUN_BASIC_CLASS CSGObject * __new_CDistantSegmentsKernel(EPrimitiveType g)
Definition: class_list.cpp:973
static SHOGUN_BASIC_CLASS CSGObject * __new_CSqrtDiagKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:949
static SHOGUN_BASIC_CLASS CSGObject * __new_CSparseVGInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:762
UI classifier.
Definition: GUIClassifier.h:24
Class CSequence to be used in the application of Structured Output (SO) learning to Hidden Markov Sup...
Class to select parameters and their ranges for model selection. The structure is organized as a tree...
class LibSVMOneClass
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralSoftmaxLayer(EPrimitiveType g)
Definition: class_list.cpp:851
static SHOGUN_BASIC_CLASS CSGObject * __new_CChi2Kernel(EPrimitiveType g)
Definition: class_list.cpp:992
static SHOGUN_BASIC_CLASS CSGObject * __new_CLatentFeatures(EPrimitiveType g)
A CNode is an element of a CTaxonomy, which is used to describe hierarchical structure between tasks...
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandomCARTree(EPrimitiveType g)
Definition: class_list.cpp:712
static SHOGUN_BASIC_CLASS CSGObject * __new_CSegmentLoss(EPrimitiveType g)
Definition: class_list.cpp:557
class to add subset support to another class. A CSubsetStackStack instance should be added and wrappe...
Definition: SubsetStack.h:37
class DiffusionMaps used to preprocess given data using Diffusion Maps dimensionality reduction techn...
Definition: DiffusionMaps.h:40
Class LinearRidgeRegression implements Ridge Regression - a regularized least square method for class...
Class that contains certain functions related to statistics, such as probability/cumulative distribut...
Definition: Statistics.h:32
A Streaming File access class.
Definition: StreamingFile.h:34
Class that contains certain methods related to numerical integration.
Definition: Integration.h:43
The Constant Kernel returns a constant for all elements.
Definition: ConstKernel.h:29
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCEDDecoder(EPrimitiveType g)
Definition: class_list.cpp:687
class F1Measure used to measure F1 score of 2-class classifier.
Class LMNN that implements the distance metric learning technique Large Margin Nearest Neighbour (LMN...
Definition: LMNN.h:37
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUILabels(EPrimitiveType g)
Definition: class_list.cpp:813
CCSOSVM.
Definition: CCSOSVM.h:43
Features that compute the Weighted Spectrum Kernel feature space explicitly.
The Chi2 kernel operating on realvalued vectors computes the chi-squared distance between sets of his...
Definition: Chi2Kernel.h:34
static SHOGUN_BASIC_CLASS CSGObject * __new_CSubset(EPrimitiveType g)
This class implements the stochastic gradient boosting algorithm for ensemble learning invented by Je...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStringFeatures(EPrimitiveType g)
Class that aggregates vector job results in each submit_result call of jobs generated from rational a...
The class BinnedDotFeatures contains a 0-1 conversion of features into bins.
class ChebyshewMetric
Class StreamingFileFromFeatures to read vector-by-vector from a CFeatures object. ...
Preprocessor PruneVarSubMean will substract the mean and remove features that have zero variance...
static SHOGUN_BASIC_CLASS CSGObject * __new_CHingeLoss(EPrimitiveType g)
Definition: class_list.cpp:935
static SHOGUN_BASIC_CLASS CSGObject * __new_CMPDSVM(EPrimitiveType g)
Definition: class_list.cpp:598
Gaussian Kernel with Automatic Relevance Detection computed on CDotFeatures.
static SHOGUN_BASIC_CLASS CSGObject * __new_CUAIFile(EPrimitiveType g)
Definition: class_list.cpp:632
static SHOGUN_BASIC_CLASS CSGObject * __new_CPluginEstimate(EPrimitiveType g)
Definition: class_list.cpp:614
static SHOGUN_BASIC_CLASS CSGObject * __new_CTaskGroup(EPrimitiveType g)
Definition: class_list.cpp:796
Class for storing MKL weights in every fold of cross-validation.
static SHOGUN_BASIC_CLASS CSGObject * __new_CParser(EPrimitiveType g)
Definition: class_list.cpp:633
Class that provides a solve method for complex dense-matrix linear systems.
The AUC kernel can be used to maximize the area under the receiver operator characteristic curve (AUC...
Definition: AUCKernel.h:35
Multiclass Labels for multi-class classification.
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultilabelAccuracy(EPrimitiveType g)
Definition: class_list.cpp:867
class UWedgeSep
Definition: UWedgeSep.h:35
Implementation of independent job that solves one of the family of shifted systems in rational approx...
class IntronList
Definition: IntronList.h:22
static SHOGUN_BASIC_CLASS CSGObject * __new_CRegressionLabels(EPrimitiveType g)
Definition: class_list.cpp:907
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskKernelMaskNormalizer(EPrimitiveType g)
Definition: class_list.cpp:797
static SHOGUN_BASIC_CLASS CSGObject * __new_CEPInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:765
the class Bessel kernel
Definition: BesselKernel.h:34
The distant segments kernel is a string kernel, which counts the number of substrings, so-called segments, at a certain distance from each other.
static SHOGUN_BASIC_CLASS CSGObject * __new_CAttenuatedEuclideanDistance(EPrimitiveType g)
Definition: class_list.cpp:737
static SHOGUN_BASIC_CLASS CSGObject * __new_CUWedge(EPrimitiveType g)
Definition: class_list.cpp:826
static SHOGUN_BASIC_CLASS CSGObject * __new_CProbitLikelihood(EPrimitiveType g)
Definition: class_list.cpp:772
Weighted Majority Vote implementation.
static SHOGUN_BASIC_CLASS CSGObject * __new_CFKFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CWaveletKernel(EPrimitiveType g)
Definition: class_list.cpp:994
static SHOGUN_BASIC_CLASS CSGObject * __new_CRecallMeasure(EPrimitiveType g)
Definition: class_list.cpp:892
Class C45ClassifierTree implements the C4.5 algorithm for decision tree learning. The algorithm steps...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassOneVsRestStrategy(EPrimitiveType g)
Definition: class_list.cpp:697
The class PolyMatchWordStringKernel computes a variant of the polynomial kernel on word-features...
class LocalityPreservingProjections used to compute embeddings of data using Locality Preserving Proj...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CDenseMatrixOperator(EPrimitiveType g)
class Multidimensionalscaling is used to perform multidimensional scaling (capable of landmark approx...
static SHOGUN_BASIC_CLASS CSGObject * __new_CTask(EPrimitiveType g)
Definition: class_list.cpp:786
The helper class to specialize base class instances of labels.
Definition: LabelsFactory.h:31
Class that is able to generate various data samples, which may be used for examples in SHOGUN...
Definition: DataGenerator.h:25
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIMath(EPrimitiveType g)
Definition: class_list.cpp:804
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianKernel(EPrimitiveType g)
Definition: class_list.cpp:998
Class CSVFile used to read data from comma-separated values (CSV) files. See http://en.wikipedia.org/wiki/Comma-separated_values.
Definition: CSVFile.h:29
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossCorrelationMeasure(EPrimitiveType g)
Definition: class_list.cpp:891
static SHOGUN_BASIC_CLASS CSGObject * __new_CSerialComputationEngine(EPrimitiveType g)
Definition: class_list.cpp:642
The dual KL approximation inference method class.
Neural layer with linear neurons, with a softmax activation function. can be only be used as an outpu...
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralLogisticLayer(EPrimitiveType g)
Definition: class_list.cpp:861
The HistogramWordString computes the TOP kernel on inhomogeneous Markov Chains.
static SHOGUN_BASIC_CLASS CSGObject * __new_CStudentsTVGLikelihood(EPrimitiveType g)
Definition: class_list.cpp:761
This class implements the quadratic time Maximum Mean Statistic as described in [1]. The MMD is the distance of two probability distributions and in a RKHS which we denote by .
static SHOGUN_BASIC_CLASS CSGObject * __new_CPolyMatchWordStringKernel(EPrimitiveType g)
Definition: class_list.cpp:974
This class can be used to convert a document collection contained in a CStringFeatures object w...
class MultitaskTraceLogisticRegression, a classifier for multitask problems. Supports only task group...
NeighborhoodPreservingEmbedding converter used to construct embeddings as described in: ...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CSet(EPrimitiveType g)
This class acts as an alternative to the CStreamingDenseFeatures class and their difference is that t...
static SHOGUN_BASIC_CLASS CSGObject * __new_CZeroMean(EPrimitiveType g)
Definition: class_list.cpp:768
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianProcessMachine(EPrimitiveType g)
Definition: class_list.cpp:743
static SHOGUN_BASIC_CLASS CSGObject * __new_CGMM(EPrimitiveType g)
Definition: class_list.cpp:898
static SHOGUN_BASIC_CLASS CSGObject * __new_CANOVAKernel(EPrimitiveType g)
Definition: class_list.cpp:987
Class for storing multiclass evaluation information in every fold of cross-validation.
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianShiftKernel(EPrimitiveType g)
Definition: class_list.cpp:995
The SingleLaplace approximation inference method class for regression and binary Classification.
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelDistance(EPrimitiveType g)
Definition: class_list.cpp:728
static SHOGUN_BASIC_CLASS CSGObject * __new_CF1Measure(EPrimitiveType g)
Definition: class_list.cpp:890
static SHOGUN_BASIC_CLASS CSGObject * __new_CGradientModelSelection(EPrimitiveType g)
Definition: class_list.cpp:678
Represents a muti-layer autoencoder.
Class ROCEvalution used to evaluate ROC (Receiver Operating Characteristic) and an area under ROC cur...
Definition: ROCEvaluation.h:32
generic linear multiclass machine
static SHOGUN_BASIC_CLASS CSGObject * __new_CFITCInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:775
Simple class which specifies the direction of gradient search.
Implementation of Leave one out cross-validation on the base of CCrossValidationSplitting. Produces subset index sets consisting of one element,for each label.
CMajorityVote is a CWeightedMajorityVote combiner, where each Machine's weight in the ensemble is 1...
Definition: MajorityVote.h:24
static SHOGUN_BASIC_CLASS CSGObject * __new_CAbsoluteDeviationLoss(EPrimitiveType g)
Definition: class_list.cpp:934
A Deep Belief Network.
static SHOGUN_BASIC_CLASS CSGObject * __new_CJADiagOrth(EPrimitiveType g)
Definition: class_list.cpp:830
Template class StringFeatures implements a list of strings.
Definition: WDSVMOcas.h:25
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIKernel(EPrimitiveType g)
Definition: class_list.cpp:811
static SHOGUN_BASIC_CLASS CSGObject * __new_CMajorityVote(EPrimitiveType g)
Definition: class_list.cpp:573
Class for reading from a string.
Definition: Parser.h:23
static SHOGUN_BASIC_CLASS CSGObject * __new_CMMDKernelSelectionMax(EPrimitiveType g)
Class SGObject is the base class of all shogun objects.
Definition: SGObject.h:112
the class CSet, a set based on the hash-table. w: http://en.wikipedia.org/wiki/Hash_table ...
Definition: Set.h:51
Class MultitaskROCEvalution used to evaluate ROC (Receiver Operating Characteristic) and an area unde...
static SHOGUN_BASIC_CLASS CSGObject * __new_CRelaxedTree(EPrimitiveType g)
Definition: class_list.cpp:705
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskClusteredLogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:783
Class that models Student's T likelihood and uses numerical integration to approximate the following ...
Features that compute the Weighted Degreee Kernel feature space explicitly.
class MultiClassSVM
Definition: MulticlassSVM.h:28
Class MultilabelCLRModel represents application specific model and contains application dependent log...
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwNativeCacheWriter(EPrimitiveType g)
Definition: class_list.cpp:606
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCStrategy(EPrimitiveType g)
Definition: class_list.cpp:694
static SHOGUN_BASIC_CLASS CSGObject * __new_CScatterKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:952
Class CFactorGraphDataGenerator Create factor graph data for multiple unit tests. ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskKernelTreeNormalizer(EPrimitiveType g)
Definition: class_list.cpp:789
static SHOGUN_BASIC_CLASS CSGObject * __new_CSparseSpatialSampleStringKernel(EPrimitiveType g)
Definition: class_list.cpp:970
static SHOGUN_BASIC_CLASS CSGObject * __new_CTanimotoDistance(EPrimitiveType g)
Definition: class_list.cpp:727
KMeans clustering, partitions the data into k (a-priori specified) clusters.
Definition: KMeans.h:57
static SHOGUN_BASIC_CLASS CSGObject * __new_CStudentsTLikelihood(EPrimitiveType g)
Definition: class_list.cpp:752
Computes the standard linear kernel on dense char valued features.
static SHOGUN_BASIC_CLASS CSGObject * __new_CSparseMultilabel(EPrimitiveType g)
Definition: class_list.cpp:553
static SHOGUN_BASIC_CLASS CSGObject * __new_CImplicitWeightedSpecFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CIndexBlock(EPrimitiveType g)
Definition: class_list.cpp:647
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwNonAdaptiveLearner(EPrimitiveType g)
Definition: class_list.cpp:611
An experimental kernel inspired by the WeightedDegreePositionStringKernel and the Gaussian kernel...
static SHOGUN_BASIC_CLASS CSGObject * __new_CGPBTSVM(EPrimitiveType g)
Definition: class_list.cpp:595
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CBinaryStream(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CPruneVarSubMean(EPrimitiveType g)
Definition: class_list.cpp:919
Class that computes eigenvalues of a real valued, self-adjoint linear operator using Lanczos algorith...
dummy data holder
Definition: Data.h:25
static SHOGUN_BASIC_CLASS CSGObject * __new_CSoftMaxLikelihood(EPrimitiveType g)
Definition: class_list.cpp:750
VwNonAdaptiveLearner uses a standard gradient descent weight update rule.
static SHOGUN_BASIC_CLASS CSGObject * __new_CBAHSIC(EPrimitiveType g)
Definition: class_list.cpp:923
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianDistribution(EPrimitiveType g)
Definition: class_list.cpp:818
static SHOGUN_BASIC_CLASS CSGObject * __new_CWRACCMeasure(EPrimitiveType g)
Definition: class_list.cpp:889
Template class that aggregates scalar job results in each submit_result call, finalize then transform...
The CommWordString kernel may be used to compute the spectrum kernel from strings that have been mapp...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultiLaplacianInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:766
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralLayer(EPrimitiveType g)
Definition: class_list.cpp:858
Class that models Probit likelihood and uses numerical integration to approximate the following varia...
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CCache(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearHMM(EPrimitiveType g)
Definition: class_list.cpp:822
static SHOGUN_BASIC_CLASS CSGObject * __new_CSquaredHingeLoss(EPrimitiveType g)
Definition: class_list.cpp:930
static SHOGUN_BASIC_CLASS CSGObject * __new_CLaRank(EPrimitiveType g)
Definition: class_list.cpp:682
CMeanRule simply averages the outputs of the Machines in the ensemble.
Definition: MeanRule.h:23
Preprocessor PNorm, normalizes vectors to have p-norm.
Definition: PNorm.h:32
static SHOGUN_BASIC_CLASS CSGObject * __new_CClusteringMutualInformation(EPrimitiveType g)
Definition: class_list.cpp:884
class AttenuatedEuclideanDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CExponentialLoss(EPrimitiveType g)
Definition: class_list.cpp:928
Class Histogram computes a histogram over all 16bit unsigned integers in the features.
Definition: Histogram.h:28
static SHOGUN_BASIC_CLASS CSGObject * __new_CBesselKernel(EPrimitiveType g)
Class UWedge.
Definition: UWedge.h:34
class FastICA
Definition: FastICA.h:33
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralInputLayer(EPrimitiveType g)
Definition: class_list.cpp:860
static SHOGUN_BASIC_CLASS CSGObject * __new_CHSIC(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelPCA(EPrimitiveType g)
Definition: class_list.cpp:926
This class implements streaming features as strings.
Implementation of maximum MMD kernel selection for combined kernel. This class selects a combination ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogRationalApproximationCGM(EPrimitiveType g)
Definition: class_list.cpp:847
static SHOGUN_BASIC_CLASS CSGObject * __new_CTDistributedStochasticNeighborEmbedding(EPrimitiveType g)
Definition: class_list.cpp:672
static SHOGUN_BASIC_CLASS CSGObject * __new_CFirstElementKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:950
LatentSVM class Latent SVM implementation based on [1]. For optimization this implementation uses SVM...
Definition: LatentSVM.h:36
static SHOGUN_BASIC_CLASS CSGObject * __new_CErrorRateMeasure(EPrimitiveType g)
Definition: class_list.cpp:887
class JensenMetric
Definition: JensenMetric.h:36
The class PolyMatchStringKernel computes a variant of the polynomial kernel on strings of same length...
static SHOGUN_BASIC_CLASS CSGObject * __new_CAvgDiagKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:953
This class is identical to the CDenseFeatures class except that it hashes each dimension to a new fea...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMKLMulticlass(EPrimitiveType g)
Definition: class_list.cpp:601
Class CFactorGraphObservation is used as the structured output.
Class for Least Angle Regression, can be used to solve LASSO.
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCAEDDecoder(EPrimitiveType g)
Definition: class_list.cpp:685
static SHOGUN_BASIC_CLASS CSGObject * __new_CDimensionReductionPreprocessor(EPrimitiveType g)
Definition: class_list.cpp:927
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossValidationResult(EPrimitiveType g)
Definition: class_list.cpp:878
#define STRING_LEN
Definition: common.h:55
static SHOGUN_BASIC_CLASS CSGObject * __new_CSOSVMHelper(EPrimitiveType g)
Definition: class_list.cpp:556
static class_list_entry_t class_list[]
static SHOGUN_BASIC_CLASS CSGObject * __new_CModelSelectionParameters(EPrimitiveType g)
Definition: class_list.cpp:676
static SHOGUN_BASIC_CLASS CSGObject * __new_CDomainAdaptationMulticlassLibLinear(EPrimitiveType g)
Definition: class_list.cpp:801
Implementation of independent jobs that solves one whole family of shifted systems in rational approx...
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingVwFeatures(EPrimitiveType g)
The Laplace approximation inference method class for multi classification.
CFactorGraphFeatures maintains an array of factor graphs, each graph is a sample, i...
static SHOGUN_BASIC_CLASS CSGObject * __new_CManhattanMetric(EPrimitiveType g)
Definition: class_list.cpp:725
This class provides an interface to the LibLinear library for large- scale linear learning focusing o...
Definition: LibLinear.h:61
Regressor used by VW.
Definition: VwRegressor.h:37
multiclass LibLinear wrapper. Uses Crammer-Singer formulation and gradient descent optimization algor...
Class CFactorDataSource Source for factor data. In some cases, the same data can be shared by many fa...
Definition: Factor.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskLeastSquaresRegression(EPrimitiveType g)
Definition: class_list.cpp:795
class CSOSVMHelper contains helper functions to compute primal objectives, dual objectives, average training losses, duality gaps etc. These values will be recorded to check convergence. This class is inspired by the matlab implementation of the block coordinate Frank-Wolfe SOSVM solver [1].
Definition: SOSVMHelper.h:31
static SHOGUN_BASIC_CLASS CSGObject * __new_CDummyFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearRidgeRegression(EPrimitiveType g)
Definition: class_list.cpp:580
static SHOGUN_BASIC_CLASS CSGObject * __new_CCSVFile(EPrimitiveType g)
Definition: class_list.cpp:634
static SHOGUN_BASIC_CLASS CSGObject * __new_CDistanceMachine(EPrimitiveType g)
Definition: class_list.cpp:745
A File access base class.
Definition: File.h:34
static SHOGUN_BASIC_CLASS CSGObject * __new_CSequence(EPrimitiveType g)
Definition: class_list.cpp:537
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogLoss(EPrimitiveType g)
Definition: class_list.cpp:936
class IndexBlock used to represent contiguous indices of one group (e.g. block of related features) ...
Definition: IndexBlock.h:25
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandomFourierDotFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultilabelSOLabels(EPrimitiveType g)
Definition: class_list.cpp:554
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralLeakyRectifiedLinearLayer(EPrimitiveType g)
Definition: class_list.cpp:863
static SHOGUN_BASIC_CLASS CSGObject * __new_CJade(EPrimitiveType g)
Definition: class_list.cpp:659
Class CBAHSIC, that extends CKernelDependenceMaximization and uses HSIC [1] to compute dependence mea...
Definition: BAHSIC.h:58
static SHOGUN_BASIC_CLASS CSGObject * __new_CDiceKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:951
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingSparseFeatures(EPrimitiveType g)
Pyramid Kernel over Chi2 matched histograms.
Definition: PyramidChi2.h:30
class SVMSGD
Definition: SVMSGD.h:36
static SHOGUN_BASIC_CLASS CSGObject * __new_CLaplacianEigenmaps(EPrimitiveType g)
Definition: class_list.cpp:663
Multiple Kernel Learning for two-class-classification.
Class MeanAbsoluteError used to compute an error of regression model.
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCIHDDecoder(EPrimitiveType g)
Definition: class_list.cpp:689
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassLibSVM(EPrimitiveType g)
Definition: class_list.cpp:703
static SHOGUN_BASIC_CLASS CSGObject * __new_CDelimiterTokenizer(EPrimitiveType g)
Definition: class_list.cpp:636
static SHOGUN_BASIC_CLASS CSGObject * __new_CQPBSVMLib(EPrimitiveType g)
Definition: class_list.cpp:593
class LocallyLinearEmbedding used to embed data using Locally Linear Embedding algorithm described in...
static SHOGUN_BASIC_CLASS CSGObject * __new_COligoStringKernel(EPrimitiveType g)
Definition: class_list.cpp:975
UI math.
Definition: GUIMath.h:22
static SHOGUN_BASIC_CLASS CSGObject * __new_CFixedDegreeStringKernel(EPrimitiveType g)
Definition: class_list.cpp:976
static SHOGUN_BASIC_CLASS CSGObject * __new_CSpectrumMismatchRBFKernel(EPrimitiveType g)
Definition: class_list.cpp:967
static SHOGUN_BASIC_CLASS CSGObject * __new_CDynProg(EPrimitiveType g)
Definition: class_list.cpp:569
Class that computes eigenvalues of a real valued, self-adjoint dense matrix linear operator using Eig...
static SHOGUN_BASIC_CLASS CSGObject * __new_CWeightedDegreeRBFKernel(EPrimitiveType g)
Definition: class_list.cpp:939
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearMachine(EPrimitiveType g)
Definition: class_list.cpp:777
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianShortRealKernel(EPrimitiveType g)
Definition: class_list.cpp:997
static SHOGUN_BASIC_CLASS CSGObject * __new_CSplineKernel(EPrimitiveType g)
Definition: class_list.cpp:985
Class CStreamingFileFromStringFeatures is derived from CStreamingFile and provides an input source fo...
static SHOGUN_BASIC_CLASS CSGObject * __new_CSingleLaplacianInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:763
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorDataSource(EPrimitiveType g)
Definition: class_list.cpp:546
Class that represents a dense-matrix linear operator. It computes matrix-vector product in its apply...
static SHOGUN_BASIC_CLASS CSGObject * __new_CCircularKernel(EPrimitiveType g)
Definition: class_list.cpp:938
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelRidgeRegression(EPrimitiveType g)
Definition: class_list.cpp:575
The Regulaty Modules kernel, based on the WD kernel, as published in Schultheiss et al...
The Weighted Degree String kernel.
CFactorGraphModel defines a model in terms of CFactorGraph and CMAPInference, where parameters are as...
static SHOGUN_BASIC_CLASS CSGObject * __new_CEuclideanDistance(EPrimitiveType g)
Definition: class_list.cpp:738
static SHOGUN_BASIC_CLASS CSGObject * __new_CRidgeKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:947
static SHOGUN_BASIC_CLASS CSGObject * __new_CWeightedCommWordStringKernel(EPrimitiveType g)
Definition: class_list.cpp:964
Sparse Spatial Sample String Kernel by Pavel Kuksa pkuksa@cs.rutgers.edu and Vladimir Pavlovic vladim...
static SHOGUN_BASIC_CLASS CSGObject * __new_CHuberLoss(EPrimitiveType g)
Definition: class_list.cpp:932
The MultitaskKernel allows Multitask Learning via a modified kernel function.
Class JADiag.
Definition: JADiag.h:35
static SHOGUN_BASIC_CLASS CSGObject * __new_CWDFeatures(EPrimitiveType g)
The well known Gaussian kernel (swiss army knife for SVMs) on dense short-real valued features...
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCLLBDecoder(EPrimitiveType g)
Definition: class_list.cpp:692
Class CHashedMultilabelModel represents application specific model and contains application dependent...
static SHOGUN_BASIC_CLASS CSGObject * __new_CKLApproxDiagonalInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:760
The Combined kernel is used to combine a number of kernels into a single CombinedKernel object by lin...
UI structure.
Definition: GUIStructure.h:28
static SHOGUN_BASIC_CLASS CSGObject * __new_CNeuralRectifiedLinearLayer(EPrimitiveType g)
Definition: class_list.cpp:856
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCRandomSparseEncoder(EPrimitiveType g)
Definition: class_list.cpp:691
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultilabelLabels(EPrimitiveType g)
Definition: class_list.cpp:908
the scatter kernel normalizer
Class KNN, an implementation of the standard k-nearest neigbor classifier.
Definition: KNN.h:56
Dynamic array class for CSGObject pointers that creates an array that can be used like a list or an a...
memory mapped emulation via binary streams (files)
Definition: BinaryStream.h:30
CSGObject * new_sgserializable(const char *sgserializable_name, EPrimitiveType generic)
static SHOGUN_BASIC_CLASS CSGObject * __new_CHashedDocConverter(EPrimitiveType g)
Definition: class_list.cpp:664
Normalize the kernel by a constant obtained from the first element of the kernel matrix, i.e. .
Class LinearMachine is a generic interface for all kinds of linear machines like classifiers.
Definition: LinearMachine.h:63
Class CustomMahalanobisDistance used to compute the distance between feature vectors and as ...
Identity Kernel Normalization, i.e. no normalization is applied.
static SHOGUN_BASIC_CLASS CSGObject * __new_CCauchyKernel(EPrimitiveType g)
Definition: class_list.cpp:991
Class CDisjointSet data structure for linking graph nodes It's easy to identify connected graph...
Definition: DisjointSet.h:26
The class MatchWordStringKernel computes a variant of the polynomial kernel on strings of same length...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassTreeGuidedLogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:681
static SHOGUN_BASIC_CLASS CSGObject * __new_CGNPPSVM(EPrimitiveType g)
Definition: class_list.cpp:596
This class implements KD-Tree. cf. http://www.autonlab.org/autonweb/14665/version/2/part/5/data/moore...
Definition: KDTree.h:45
static SHOGUN_BASIC_CLASS CSGObject * __new_CDomainAdaptationSVMLinear(EPrimitiveType g)
Definition: class_list.cpp:802
Normalize the kernel by adding a constant term to its diagonal. This aids kernels to become positive ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CGridSearchModelSelection(EPrimitiveType g)
Definition: class_list.cpp:679
class MultitaskL12LogisticRegression, a classifier for multitask problems. Supports only task group r...
static SHOGUN_BASIC_CLASS CSGObject * __new_CHashedDocDotFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CNewtonSVM(EPrimitiveType g)
Definition: class_list.cpp:590
Class CSparseMultilabel to be used in the application of Structured Output (SO) learning to Multilabe...
class BALMeasure used to measure balanced error of 2-class classifier.
Class NearestCentroid, an implementation of Nearest Shrunk Centroid classifier.
static SHOGUN_BASIC_CLASS CSGObject * __new_CIndividualJobResultAggregator(EPrimitiveType g)
Definition: class_list.cpp:845
A Binary file access class.
Definition: BinaryFile.h:30
static SHOGUN_BASIC_CLASS CSGObject * __new_CIOBuffer(EPrimitiveType g)
Definition: class_list.cpp:631
SimpleLocalityImprovedString kernel, is a ``simplified'' and better performing version of the Localit...
class GPBTSVM
Definition: GPBTSVM.h:23
static SHOGUN_BASIC_CLASS CSGObject * __new_CSalzbergWordStringKernel(EPrimitiveType g)
Definition: class_list.cpp:982
Class that models dual variational logit likelihood.
static SHOGUN_BASIC_CLASS CSGObject * __new_CMeanSquaredLogError(EPrimitiveType g)
Definition: class_list.cpp:877
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibSVMFile(EPrimitiveType g)
Definition: class_list.cpp:628
static SHOGUN_BASIC_CLASS CSGObject * __new_CStratifiedCrossValidationSplitting(EPrimitiveType g)
Definition: class_list.cpp:881
static SHOGUN_BASIC_CLASS CSGObject * __new_CMeanRule(EPrimitiveType g)
Definition: class_list.cpp:572
static SHOGUN_BASIC_CLASS CSGObject * __new_CSparseInverseCovariance(EPrimitiveType g)
Definition: class_list.cpp:824
static SHOGUN_BASIC_CLASS CSGObject * __new_CSparseEuclideanDistance(EPrimitiveType g)
Definition: class_list.cpp:726
static SHOGUN_BASIC_CLASS CSGObject * __new_CProductKernel(EPrimitiveType g)
Definition: class_list.cpp:996
class SpecificityMeasure used to measure specificity of 2-class classifier.
The MultitaskKernel allows learning a piece-wise linear function (PLIF) via MKL.
class WRACCMeasure used to measure weighted relative accuracy of 2-class classifier.
static SHOGUN_BASIC_CLASS CSGObject * __new_CPolyMatchStringKernel(EPrimitiveType g)
Definition: class_list.cpp:960
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwEnvironment(EPrimitiveType g)
Definition: class_list.cpp:608
ZeroMeanCenterKernelNormalizer centers the kernel in feature space.
Class that holds ONE combination of parameters for a learning machine. The structure is organized as ...
Features that compute the Spectrum Kernel feature space explicitly.
The Const mean function class.
Definition: ConstMean.h:48
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIPluginEstimate(EPrimitiveType g)
Definition: class_list.cpp:812
static SHOGUN_BASIC_CLASS CSGObject * __new_CStructuredOutputMachine(EPrimitiveType g)
Definition: class_list.cpp:778
static SHOGUN_BASIC_CLASS CSGObject * __new_CID3ClassifierTree(EPrimitiveType g)
Definition: class_list.cpp:704
Class that models Logit likelihood and uses numerical integration to approximate the following variat...
Class StreamingVwCacheFile to read vector-by-vector from VW cache files.
The well known Gaussian kernel (swiss army knife for SVMs) computed on CDotFeatures.
Class CStochasticSOSVM solves SOSVM using stochastic subgradient descent on the SVM primal problem [1...
static SHOGUN_BASIC_CLASS CSGObject * __new_CHierarchicalMultilabelModel(EPrimitiveType g)
Definition: class_list.cpp:549
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CMemoryMappedFile(EPrimitiveType g)
This class implements streaming features for use with VW.
static SHOGUN_BASIC_CLASS CSGObject * __new_CSphericalKernel(EPrimitiveType g)
Definition: class_list.cpp:940
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwAdaptiveLearner(EPrimitiveType g)
Definition: class_list.cpp:610
The Distance kernel takes a distance as input.
class HessianLocallyLinearEmbedding used to preprocess data using Hessian Locally Linear Embedding al...
Preprocessor RescaleFeautres is rescaling the range of features to make the features independent of e...
static SHOGUN_BASIC_CLASS CSGObject * __new_CCanberraWordDistance(EPrimitiveType g)
Definition: class_list.cpp:731
The class TOPFeatures implements TOP kernel features obtained from two Hidden Markov models...
Definition: TOPFeatures.h:70
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCOVOEncoder(EPrimitiveType g)
Definition: class_list.cpp:693
static SHOGUN_BASIC_CLASS CSGObject * __new_CROCEvaluation(EPrimitiveType g)
Definition: class_list.cpp:865
class RecallMeasure used to measure recall of 2-class classifier.
Class CMAPInference performs MAP inference on a factor graph. Briefly, given a factor graph model...
Definition: MAPInference.h:46
static SHOGUN_BASIC_CLASS CSGObject * __new_CTaxonomy(EPrimitiveType g)
Definition: class_list.cpp:788
static SHOGUN_BASIC_CLASS CSGObject * __new_CIdentityKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:946
static SHOGUN_BASIC_CLASS CSGObject * __new_CQuadraticTimeMMD(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CGradientResult(EPrimitiveType g)
Definition: class_list.cpp:868
static SHOGUN_BASIC_CLASS CSGObject * __new_CConjugateGradientSolver(EPrimitiveType g)
Definition: class_list.cpp:837
Implementation of stratified cross-validation on the base of CSplittingStrategy. Produces subset inde...
static SHOGUN_BASIC_CLASS CSGObject * __new_CPRCEvaluation(EPrimitiveType g)
Definition: class_list.cpp:882
static SHOGUN_BASIC_CLASS CSGObject * __new_CFWSOSVM(EPrimitiveType g)
Definition: class_list.cpp:552
This class implements the Hilbert Schmidtd Independence Criterion based independence test as describe...
Definition: HSIC.h:91
The KL approximation inference method class.
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelStructuredOutputMachine(EPrimitiveType g)
Definition: class_list.cpp:741
static SHOGUN_BASIC_CLASS CSGObject * __new_CCustomMahalanobisDistance(EPrimitiveType g)
Definition: class_list.cpp:732
class MultitaskLinearMachine, a base class for linear multitask classifiers
static SHOGUN_BASIC_CLASS CSGObject * __new_CAveragedPerceptron(EPrimitiveType g)
Definition: class_list.cpp:612
Class MeanSquaredError used to compute an error of regression model.
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CParseBuffer(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CStatistics(EPrimitiveType g)
Definition: class_list.cpp:831
This class implements the Classification And Regression Trees algorithm by Breiman et al for decision...
Definition: CARTree.h:79
Class that models a Student's-t likelihood.
: Pseudo random number geneartor
Definition: Random.h:34
static SHOGUN_BASIC_CLASS CSGObject * __new_CFFSep(EPrimitiveType g)
Definition: class_list.cpp:660
static SHOGUN_BASIC_CLASS CSGObject * __new_CGNPPLib(EPrimitiveType g)
Definition: class_list.cpp:591
Class LibSVR, performs support vector regression using LibSVM.
Definition: LibSVR.h:70
static SHOGUN_BASIC_CLASS CSGObject * __new_CMeanShiftDataGenerator(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CMeanSquaredError(EPrimitiveType g)
Definition: class_list.cpp:872
static SHOGUN_BASIC_CLASS CSGObject * __new_CSortWordString(EPrimitiveType g)
Definition: class_list.cpp:917
UI converter.
Definition: GUIConverter.h:24
Class StreamingVwFile to read vector-by-vector from Vowpal Wabbit data files. It reads the example an...
static SHOGUN_BASIC_CLASS CSGObject * __new_CDistanceKernel(EPrimitiveType g)
Definition: class_list.cpp:984
This class implements randomized CART algorithm used in the tree growing process of candidate trees i...
Definition: RandomCARTree.h:48
class Bray-Curtis distance
The class DenseFeatures implements dense feature matrices.
Definition: LDA.h:41
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorGraphModel(EPrimitiveType g)
Definition: class_list.cpp:567
The KL approximation inference method class.
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CDenseSubSamplesFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandomConditionalProbabilityTree(EPrimitiveType g)
Definition: class_list.cpp:709
static SHOGUN_BASIC_CLASS CSGObject * __new_CIntronList(EPrimitiveType g)
Definition: class_list.cpp:551
class LaplacianEigenmaps used to construct embeddings of data using Laplacian Eigenmaps algorithm as ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CPeriodicKernel(EPrimitiveType g)
Definition: class_list.cpp:986
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianBlobsDataGenerator(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CHessianLocallyLinearEmbedding(EPrimitiveType g)
Definition: class_list.cpp:665
The KL approximation inference method class.
static SHOGUN_BASIC_CLASS CSGObject * __new_CMKLRegression(EPrimitiveType g)
Definition: class_list.cpp:577
static SHOGUN_BASIC_CLASS CSGObject * __new_CAutoencoder(EPrimitiveType g)
Definition: class_list.cpp:862
static SHOGUN_BASIC_CLASS CSGObject * __new_CLBPPyrDotFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogitLikelihood(EPrimitiveType g)
Definition: class_list.cpp:767
The class DummyFeatures implements features that only know the number of feature objects (but don't a...
Definition: DummyFeatures.h:25
Features that compute the Weighted Degreee Kernel feature space explicitly.
Definition: SNPFeatures.h:29
Class Perceptron implements the standard linear (online) perceptron.
Definition: Perceptron.h:31
static SHOGUN_BASIC_CLASS CSGObject * __new_CC45ClassifierTree(EPrimitiveType g)
Definition: class_list.cpp:710
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelLocallyLinearEmbedding(EPrimitiveType g)
Definition: class_list.cpp:669
ScatterSVM - Multiclass SVM.
Definition: ScatterSVM.h:49
File based string features.
Represents an input layer. The layer can be either connected to all the input features that a network...
Neural layer with linear neurons, with an identity activation function. can be used as a hidden layer...
CSquaredLoss implements the squared loss function.
Definition: SquaredLoss.h:29
Neural layer with linear neurons, with a logistic activation function. can be used as a hidden layer ...
class ErrorRateMeasure used to measure error rate of 2-class classifier.
Class GaussianNaiveBayes, a Gaussian Naive Bayes classifier.
SqrtDiagKernelNormalizer divides by the Square Root of the product of the diagonal elements...
static SHOGUN_BASIC_CLASS CSGObject * __new_CTime(EPrimitiveType g)
Definition: class_list.cpp:648
static SHOGUN_BASIC_CLASS CSGObject * __new_CPolyFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CJobResult(EPrimitiveType g)
Definition: class_list.cpp:641
Preprocessor NormOne, normalizes vectors to have norm 1.
Definition: NormOne.h:34
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorGraphFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIHMM(EPrimitiveType g)
Definition: class_list.cpp:806
static SHOGUN_BASIC_CLASS CSGObject * __new_CHierarchical(EPrimitiveType g)
Definition: class_list.cpp:897
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUITime(EPrimitiveType g)
Definition: class_list.cpp:808
Model selection class which searches for the best model by a random search. See CModelSelection for d...
static SHOGUN_BASIC_CLASS CSGObject * __new_CShareBoost(EPrimitiveType g)
Definition: class_list.cpp:695
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingFileFromFeatures(EPrimitiveType g)
Definition: class_list.cpp:622
Class implementing a purely online version of CLibLinear, using the L2R_L1LOSS_SVC_DUAL solver only...
Dense version of the well-known Gaussian probability distribution, defined as .
Base class that stores the result of an independent job when the result is a vector.
Preprocessor KernelPCA performs kernel principal component analysis.
Definition: KernelPCA.h:35
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwRegressor(EPrimitiveType g)
Definition: class_list.cpp:605
Main component in convolutional neural networks
static SHOGUN_BASIC_CLASS CSGObject * __new_CTStudentKernel(EPrimitiveType g)
Definition: class_list.cpp:989
The Isomap class is used to embed data using Isomap algorithm as described in:
Definition: Isomap.h:59
class ID3ClassifierTree, implements classifier tree for discrete feature values using the ID3 algorit...
static SHOGUN_BASIC_CLASS CSGObject * __new_CIsomap(EPrimitiveType g)
Definition: class_list.cpp:673
Class of the Expectation Propagation (EP) posterior approximation inference method.
The class CDelimiterTokenizer is used to tokenize a SGVector into tokens using custom chars as ...
read sparse real valued features in svm light format e.g. -1 1:10.0 2:100.2 1000:1.3 with -1 == (optional) label and dim 1 - value 10.0 dim 2 - value 100.2 dim 1000 - value 1.3
Definition: LibSVMFile.h:34
multiclass OCAS wrapper
static SHOGUN_BASIC_CLASS CSGObject * __new_CSGDQN(EPrimitiveType g)
Definition: class_list.cpp:588
static SHOGUN_BASIC_CLASS CSGObject * __new_CPlif(EPrimitiveType g)
Definition: class_list.cpp:543
static SHOGUN_BASIC_CLASS CSGObject * __new_CHistogramWordStringKernel(EPrimitiveType g)
Definition: class_list.cpp:980
Power kernel.
Definition: PowerKernel.h:35
class SGDQN
Definition: SGDQN.h:36
static SHOGUN_BASIC_CLASS CSGObject * __new_CTOPFeatures(EPrimitiveType g)
Container class that returns results from GradientEvaluation. It contains the function value as well ...
Class CFactorGraph a factor graph is a structured input in general.
Definition: FactorGraph.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CTableFactorType(EPrimitiveType g)
Definition: class_list.cpp:542
Class that represents a sparse-matrix linear operator. It computes matrix-vector product in its appl...
Class for outputting cross-validation intermediate results to the standard output. Simply prints all messages it gets.
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultilabelCLRModel(EPrimitiveType g)
Definition: class_list.cpp:568
static SHOGUN_BASIC_CLASS CSGObject * __new_CSpectrumRBFKernel(EPrimitiveType g)
Definition: class_list.cpp:963
Normalize the kernel by either a constant or the average value of the diagonal elements (depending on...
static SHOGUN_BASIC_CLASS CSGObject * __new_CThresholdRejectionStrategy(EPrimitiveType g)
Definition: class_list.cpp:714
static SHOGUN_BASIC_CLASS CSGObject * __new_CHMM(EPrimitiveType g)
Definition: class_list.cpp:815
static SHOGUN_BASIC_CLASS CSGObject * __new_CMMDKernelSelectionOpt(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CLabelsFactory(EPrimitiveType g)
Definition: class_list.cpp:906
Class GMNPSVM implements a one vs. rest MultiClass SVM.
Definition: GMNPSVM.h:26
Preprocessor HomogeneousKernelMap performs homogeneous kernel maps as described in.
static SHOGUN_BASIC_CLASS CSGObject * __new_CVarianceKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:954
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianARDSparseKernel(EPrimitiveType g)
Definition: class_list.cpp:757
Class that provides a sample method for Gaussian samples.
Definition: NormalSampler.h:22
static SHOGUN_BASIC_CLASS CSGObject * __new_CData(EPrimitiveType g)
Definition: class_list.cpp:635
class SubsequenceStringKernel that implements String Subsequence Kernel (SSK) discussed by Lodhi et...
Class ListElement, defines how an element of the the list looks like.
Definition: List.h:25
static SHOGUN_BASIC_CLASS CSGObject * __new_CMinimizerContext(EPrimitiveType g)
Definition: class_list.cpp:617
Class PRCEvaluation used to evaluate PRC (Precision Recall Curve) and an area under PRC curve (auPRC)...
Definition: PRCEvaluation.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultilabelModel(EPrimitiveType g)
Definition: class_list.cpp:560
static SHOGUN_BASIC_CLASS CSGObject * __new_CHistogram(EPrimitiveType g)
Definition: class_list.cpp:817
#define PT_NOT_GENERIC
Definition: DataType.h:21
Class CMatrixFeatures used to represent data whose feature vectors are better represented with matric...
static SHOGUN_BASIC_CLASS CSGObject * __new_CHashedWDFeaturesTransposed(EPrimitiveType g)
Class CMultilabelAccuracy used to compute accuracy of multilabel classification.
class OnlineSVMSGD
Definition: OnlineSVMSGD.h:35
static SHOGUN_BASIC_CLASS CSGObject * __new_CSVM(EPrimitiveType g)
Definition: class_list.cpp:585
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianLikelihood(EPrimitiveType g)
Definition: class_list.cpp:754
Class CSquaredHingeLoss implements a squared hinge loss function.
Class Jedi.
Definition: JediDiag.h:34
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogitVGPiecewiseBoundLikelihood(EPrimitiveType g)
Definition: class_list.cpp:770
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskKernelMaskPairNormalizer(EPrimitiveType g)
Definition: class_list.cpp:785
static SHOGUN_BASIC_CLASS CSGObject * __new_CCombinedFeatures(EPrimitiveType g)
The Fully Independent Conditional Training inference method class.
static SHOGUN_BASIC_CLASS CSGObject * __new_CPNorm(EPrimitiveType g)
Definition: class_list.cpp:915
static SHOGUN_BASIC_CLASS CSGObject * __new_CCrossValidationMulticlassStorage(EPrimitiveType g)
Definition: class_list.cpp:895
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingVwCacheFile(EPrimitiveType g)
Definition: class_list.cpp:621
class CStructuredAccuracy used to compute accuracy of structured classification
static SHOGUN_BASIC_CLASS CSGObject * __new_CJensenMetric(EPrimitiveType g)
Definition: class_list.cpp:723
static SHOGUN_BASIC_CLASS CSGObject * __new_CSigmoidKernel(EPrimitiveType g)
Definition: class_list.cpp:937
The class RealFileFeatures implements a dense double-precision floating point matrix from a file...
static SHOGUN_BASIC_CLASS CSGObject * __new_CFeatureBlockLogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:616
Class for work with binary file in protobuf format.
Definition: ProtobufFile.h:53
Class CLogLossMargin implements a margin-based log-likelihood loss function.
Definition: LogLossMargin.h:24
class TaskTree used to represent a tree of tasks. Tree is constructed via task with subtasks (and sub...
Definition: TaskTree.h:27
static SHOGUN_BASIC_CLASS CSGObject * __new_CProbingSampler(EPrimitiveType g)
Definition: class_list.cpp:840
class MahalanobisDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CMinkowskiMetric(EPrimitiveType g)
Definition: class_list.cpp:736
Class evaluates a machine using its associated differentiable function for the function value and its...
This class implements the random fourier features for the DotFeatures framework. Basically upon the o...
Wave kernel.
Definition: WaveKernel.h:35
class PluginEstimate
Class CTableFactorType the way that store assignments of variables and energies in a table or a multi...
Definition: FactorType.h:122
static SHOGUN_BASIC_CLASS CSGObject * __new_CListElement(EPrimitiveType g)
Definition: class_list.cpp:650
Preprocessor PCA performs principial component analysis on input feature vectors/matrices. When the init method in PCA is called with proper feature matrix X (with say N number of vectors and D feature dimension), a transformation matrix is computed and stored internally. This transformation matrix is then used to transform all D-dimensional feature vectors or feature matrices (with D feature dimensions) supplied via apply_to_feature_matrix or apply_to_feature_vector methods. This tranformation outputs the T-Dimensional approximation of all these input vectors and matrices (where T<=min(D,N)). The transformation matrix is essentially a DxT matrix, the columns of which correspond to the eigenvectors of the covariance matrix(XX') having top T eigenvalues.
Definition: PCA.h:113
Kernel selection class that selects the single kernel that maximises the MMD statistic. Works for CQuadraticTimeMMD and CLinearTimeMMD. This leads to a heuristic that is better than the standard median heuristic for Gaussian kernels. However, it comes with no guarantees.
static SHOGUN_BASIC_CLASS CSGObject * __new_CLocallyLinearEmbedding(EPrimitiveType g)
Definition: class_list.cpp:671
static SHOGUN_BASIC_CLASS CSGObject * __new_CSingleFITCLaplacianInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:751
static SHOGUN_BASIC_CLASS CSGObject * __new_CRationalApproximationIndividualJob(EPrimitiveType g)
Definition: class_list.cpp:843
static SHOGUN_BASIC_CLASS CSGObject * __new_CKDTree(EPrimitiveType g)
Definition: class_list.cpp:711
Class Signal implements signal handling to e.g. allow ctrl+c to cancel a long running process...
Definition: Signal.h:48
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingFileFromSparseFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskTraceLogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:790
static SHOGUN_BASIC_CLASS CSGObject * __new_CDeepBeliefNetwork(EPrimitiveType g)
Definition: class_list.cpp:859
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStringFileFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CSpecificityMeasure(EPrimitiveType g)
Definition: class_list.cpp:894
static SHOGUN_BASIC_CLASS CSGObject * __new_CBalancedConditionalProbabilityTree(EPrimitiveType g)
Definition: class_list.cpp:706
The Laplace approximation inference method with LBFGS class for regression and binary classification...
Dynamic Programming Class.
Definition: DynProg.h:74
This class implements the linear time Maximum Mean Statistic as described in [1] for streaming data (...
Definition: LinearTimeMMD.h:66
Features that allow stacking of a number of DotFeatures.
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactor(EPrimitiveType g)
Definition: class_list.cpp:547
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CVectorResult(EPrimitiveType g)
Class CVowpalWabbit is the implementation of the online learning algorithm used in Vowpal Wabbit...
Definition: VowpalWabbit.h:40
static SHOGUN_BASIC_CLASS CSGObject * __new_CNormOne(EPrimitiveType g)
Definition: class_list.cpp:924
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibSVM(EPrimitiveType g)
Definition: class_list.cpp:597
A generic Support Vector Machine Interface.
Definition: SVM.h:49
static SHOGUN_BASIC_CLASS CSGObject * __new_CLanczosEigenSolver(EPrimitiveType g)
Definition: class_list.cpp:849
UI features.
Definition: GUIFeatures.h:36
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelMulticlassMachine(EPrimitiveType g)
Definition: class_list.cpp:748
Class which collects generic mathematical functions.
Definition: Math.h:134
static SHOGUN_BASIC_CLASS CSGObject * __new_CSubsequenceStringKernel(EPrimitiveType g)
Definition: class_list.cpp:979
static SHOGUN_BASIC_CLASS CSGObject * __new_CMAPInference(EPrimitiveType g)
Definition: class_list.cpp:562
Features that compute the Weighted Degreee Kernel feature space explicitly.
the LaRank multiclass SVM machine
Definition: LaRank.h:306
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CStreamingDenseFeatures(EPrimitiveType g)
class GeodesicMetric
Implements MMD kernel selection for a number of Gaussian baseline kernels via selecting the one with ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CNode(EPrimitiveType g)
Definition: class_list.cpp:787
static SHOGUN_BASIC_CLASS CSGObject * __new_CStreamingVwFile(EPrimitiveType g)
Definition: class_list.cpp:623
static SHOGUN_BASIC_CLASS CSGObject * __new_CPrecisionMeasure(EPrimitiveType g)
Definition: class_list.cpp:893
Template class Cache implements a simple cache.
the class WaveletKernel
Definition: WaveletKernel.h:37
static SHOGUN_BASIC_CLASS CSGObject * __new_CHashedMultilabelModel(EPrimitiveType g)
Definition: class_list.cpp:540
Binary Labels for binary classification.
Definition: BinaryLabels.h:37
Preprocessor CRandomFourierGaussPreproc implements Random Fourier Features for the Gauss kernel a la ...
Cauchy kernel.
Definition: CauchyKernel.h:35
The HistogramIntersection kernel operating on realvalued vectors computes the histogram intersection ...
class SVMOcas
Definition: SVMOcas.h:34
Implementation of normal cross-validation on the base of CSplittingStrategy. Produces subset index se...
Preprocessor that decompresses compressed strings.
CHingeLoss implements the hinge loss function.
Definition: HingeLoss.h:29
static SHOGUN_BASIC_CLASS CSGObject * __new_CHMSVMModel(EPrimitiveType g)
Definition: class_list.cpp:559
static SHOGUN_BASIC_CLASS CSGObject * __new_CPerceptron(EPrimitiveType g)
Definition: class_list.cpp:615
CHuberLoss implements the Huber loss function. It behaves like SquaredLoss function at values below H...
Definition: HuberLoss.h:44
static SHOGUN_BASIC_CLASS CSGObject * __new_CMKLClassification(EPrimitiveType g)
Definition: class_list.cpp:603
domain adaptation multiclass LibLinear wrapper Source domain is assumed to b
class QPBSVMLib
Definition: QPBSVMLib.h:42
static SHOGUN_BASIC_CLASS CSGObject * __new_CSumOne(EPrimitiveType g)
Definition: class_list.cpp:921
: Bagging algorithm i.e. bootstrap aggregating
static SHOGUN_BASIC_CLASS CSGObject * __new_CList(EPrimitiveType g)
Definition: class_list.cpp:651
static SHOGUN_BASIC_CLASS CSGObject * __new_CLinearLocalTangentSpaceAlignment(EPrimitiveType g)
Definition: class_list.cpp:670
NewtonSVM, In this Implementation linear SVM is trained in its primal form using Newton-like iteratio...
Definition: NewtonSVM.h:29
static SHOGUN_BASIC_CLASS CSGObject * __new_CSubsetStack(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCDiscriminantEncoder(EPrimitiveType g)
Definition: class_list.cpp:686
class GNPPSVM
Definition: GNPPSVM.h:21
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CHashedSparseFeatures(EPrimitiveType g)
implement DotFeatures for the polynomial kernel
Definition: PolyFeatures.h:27
clustering (normalized) mutual information
The Custom Distance allows for custom user provided distance matrices.
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianProcessRegression(EPrimitiveType g)
Definition: class_list.cpp:574
used to estimate inverse covariance matrix using graphical lasso
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassModel(EPrimitiveType g)
Definition: class_list.cpp:544
Class that provides a solve method for real sparse-matrix linear systems using LLT.
class TreeMachine, a base class for tree based multiclass classifiers. This class is derived from CBa...
Definition: TreeMachine.h:48
static SHOGUN_BASIC_CLASS CSGObject * __new_CMatchWordStringKernel(EPrimitiveType g)
Definition: class_list.cpp:965
multiclass one vs rest strategy used to train generic multiclass machines for K-class problems with b...
The Weighted Degree Position String kernel (Weighted Degree kernel with shifts).
static SHOGUN_BASIC_CLASS CSGObject * __new_CKernelMeanMatching(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CMKLOneClass(EPrimitiveType g)
Definition: class_list.cpp:602
implement DotFeatures for the polynomial kernel
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassAccuracy(EPrimitiveType g)
Definition: class_list.cpp:869
Neural layer with rectified linear neurons.
A class to construct neural layers.
Definition: NeuralLayers.h:52
static SHOGUN_BASIC_CLASS CSGObject * __new_CRandomForest(EPrimitiveType g)
Definition: class_list.cpp:742
class CanberraMetric
static SHOGUN_BASIC_CLASS CSGObject * __new_CAccuracyMeasure(EPrimitiveType g)
Definition: class_list.cpp:886
Preprocessor SortWordString, sorts the indivual strings in ascending order.
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CSparseMatrixOperator(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CMCLDA(EPrimitiveType g)
Definition: class_list.cpp:719
class CanberraWordDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CKLCovarianceInferenceMethod(EPrimitiveType g)
Definition: class_list.cpp:773
This class implements streaming features with sparse feature vectors. The vector is represented as an...
static SHOGUN_BASIC_CLASS CSGObject * __new_CGradientEvaluation(EPrimitiveType g)
Definition: class_list.cpp:873
static SHOGUN_BASIC_CLASS CSGObject * __new_CGUIClassifier(EPrimitiveType g)
Definition: class_list.cpp:814
static SHOGUN_BASIC_CLASS CSGObject * __new_CClusteringAccuracy(EPrimitiveType g)
Definition: class_list.cpp:880
Implements Local Binary Patterns with Scale Pyramids as dot features for a set of images...
static SHOGUN_BASIC_CLASS CSGObject * __new_CSequenceLabels(EPrimitiveType g)
Definition: class_list.cpp:538
UI distance.
Definition: GUIDistance.h:25
Circular kernel.
Multilabel Labels for multi-label classification.
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CSparseFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CRationalApproximationCGMJob(EPrimitiveType g)
Definition: class_list.cpp:844
static SHOGUN_BASIC_CLASS CSGObject * __new_CLatentSOSVM(EPrimitiveType g)
Definition: class_list.cpp:900
#define SHOGUN_TEMPLATE_CLASS
Definition: class_list.cpp:535
static SHOGUN_BASIC_CLASS CSGObject * __new_CVwNativeCacheReader(EPrimitiveType g)
Definition: class_list.cpp:607
This class can be used to provide on-the-fly vectorization of a document collection. Like in the standard Bag-of-Words representation, this class considers each document as a collection of tokens, which are then hashed into a new feature space of a specified dimension. This class is very flexible and allows the user to specify the tokenizer used to tokenize each document, specify whether the results should be normalized with regards to the sqrt of the document size, as well as to specify whether he wants to combine different tokens. The latter implements a k-skip n-grams approach, meaning that you can combine up to n tokens, while skipping up to k. Eg. for the tokens ["a", "b", "c", "d"], with n_grams = 2 and skips = 2, one would get the following combinations : ["a", "ab", "ac" (skipped 1), "ad" (skipped 2), "b", "bc", "bd" (skipped 1), "c", "cd", "d"].
static SHOGUN_TEMPLATE_CLASS CSGObject * __new_CDecompressString(EPrimitiveType g)
This class implements the Random Forests algorithm. In Random Forests algorithm, we train a number of...
Definition: RandomForest.h:46
static SHOGUN_BASIC_CLASS CSGObject * __new_CHash(EPrimitiveType g)
Definition: class_list.cpp:640
abstract class for latent labels As latent labels always depends on the given application, this class only defines the API that the user has to implement for latent labels.
Definition: LatentLabels.h:26
The LocalAlignmentString kernel compares two sequences through all possible local alignments between ...
static SHOGUN_BASIC_CLASS CSGObject * __new_CECOCOVREncoder(EPrimitiveType g)
Definition: class_list.cpp:688
static SHOGUN_BASIC_CLASS CSGObject * __new_CPowerKernel(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CVowpalWabbit(EPrimitiveType g)
Definition: class_list.cpp:604
Class that contains methods for computing Jacobi elliptic functions related to complex analysis...
Class CMulticlassSOLabels to be used in the application of Structured Output (SO) learning to multicl...
class FFSep
Definition: FFSep.h:36
The class CombinedFeatures is used to combine a number of of feature objects into a single CombinedFe...
static SHOGUN_BASIC_CLASS CSGObject * __new_CConstKernel(EPrimitiveType g)
Definition: class_list.cpp:958
static SHOGUN_BASIC_CLASS CSGObject * __new_CIndexBlockTree(EPrimitiveType g)
Definition: class_list.cpp:645
Implementaion of rational approximation of a operator-function times vector where the operator functi...
The inference method class based on the Titsias' variational bound. For more details, see Titsias, Michalis K. "Variational learning of inducing variables in sparse Gaussian processes." International Conference on Artificial Intelligence and Statistics. 2009.
Class CHierarchicalMultilabelModel represents application specific model and contains application dep...
Class CStreamingFileFromSparseFeatures is derived from CStreamingFile and provides an input source fo...
static SHOGUN_BASIC_CLASS CSGObject * __new_CDirectEigenSolver(EPrimitiveType g)
Definition: class_list.cpp:850
class CManifoldSculpting used to embed data using manifold sculpting embedding algorithm.
class PlifArray
Definition: PlifArray.h:25
Gaussian Mixture Model interface.
Definition: GMM.h:40
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibSVR(EPrimitiveType g)
Definition: class_list.cpp:578
static SHOGUN_BASIC_CLASS CSGObject * __new_CTron(EPrimitiveType g)
Definition: class_list.cpp:618
Log kernel.
Definition: LogKernel.h:35
Class CMulticlassModel that represents the application specific model and contains the application de...
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianProcessClassification(EPrimitiveType g)
Definition: class_list.cpp:613
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogLossMargin(EPrimitiveType g)
Definition: class_list.cpp:929
Hidden Markov Model.
Definition: HMM.h:369
This class provides an interface to the LibLinear library for large- scale linear learning focusing o...
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassOneVsOneStrategy(EPrimitiveType g)
Definition: class_list.cpp:716
static SHOGUN_BASIC_CLASS CSGObject * __new_CRBM(EPrimitiveType g)
Definition: class_list.cpp:864
static SHOGUN_BASIC_CLASS CSGObject * __new_CManhattanWordDistance(EPrimitiveType g)
Definition: class_list.cpp:721
Class UAIFILE used to read data from UAI files. See http://graphmod.ics.uci.edu/uai08/FileFormat for ...
Definition: UAIFile.h:27
Class CFactor A factor is defined on a clique in the factor graph. Each factor can have its own data...
Definition: Factor.h:89
static SHOGUN_BASIC_CLASS CSGObject * __new_CGeodesicMetric(EPrimitiveType g)
Definition: class_list.cpp:739
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskKernelNormalizer(EPrimitiveType g)
Definition: class_list.cpp:791
Base class of the components of StructuredLabels.
class EuclideanDistance
static SHOGUN_BASIC_CLASS CSGObject * __new_CGMNPLib(EPrimitiveType g)
Definition: class_list.cpp:680
static SHOGUN_BASIC_CLASS CSGObject * __new_CHammingWordDistance(EPrimitiveType g)
Definition: class_list.cpp:733
CLogLoss implements the logarithmic loss function.
Definition: LogLoss.h:24
VarianceKernelNormalizer divides by the ``variance''.
static SHOGUN_BASIC_CLASS CSGObject * __new_CPlifMatrix(EPrimitiveType g)
Definition: class_list.cpp:563
Collection of Hashing Functions.
Definition: Hash.h:50
static SHOGUN_BASIC_CLASS CSGObject * __new_CSVMOcas(EPrimitiveType g)
Definition: class_list.cpp:583
static SHOGUN_BASIC_CLASS CSGObject * __new_CMath(EPrimitiveType g)
Definition: class_list.cpp:833
The class LinearHMM is for learning Higher Order Markov chains.
Definition: LinearHMM.h:41
Class List implements a doubly connected list for low-level-objects.
Definition: List.h:84
static SHOGUN_BASIC_CLASS CSGObject * __new_CMMDKernelSelectionCombOpt(EPrimitiveType g)
The class FKFeatures implements Fischer kernel features obtained from two Hidden Markov models...
Definition: FKFeatures.h:43
static SHOGUN_BASIC_CLASS CSGObject * __new_CFactorAnalysis(EPrimitiveType g)
Definition: class_list.cpp:668
static SHOGUN_BASIC_CLASS CSGObject * __new_CMultitaskL12LogisticRegression(EPrimitiveType g)
Definition: class_list.cpp:793
The LocalityImprovedString kernel is inspired by the polynomial kernel. Comparing neighboring charact...
store plif arrays for all transitions in the model
Definition: PlifMatrix.h:31
Class that models Probit likelihood.
static SHOGUN_BASIC_CLASS CSGObject * __new_CIndexFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CChebyshewMetric(EPrimitiveType g)
Definition: class_list.cpp:722
Preprocessor SumOne, normalizes vectors to have sum 1.
Definition: SumOne.h:32
This is the generic class for mixture models. The final distribution is a mixture of various simple d...
Definition: MixtureModel.h:44
static SHOGUN_BASIC_CLASS CSGObject * __new_CStochasticGBMachine(EPrimitiveType g)
Definition: class_list.cpp:782
static SHOGUN_BASIC_CLASS CSGObject * __new_CWeightedMajorityVote(EPrimitiveType g)
Definition: class_list.cpp:571
static SHOGUN_BASIC_CLASS CSGObject * __new_CLatentLabels(EPrimitiveType g)
Definition: class_list.cpp:909
The zero mean function class.
Definition: ZeroMean.h:46
Class CVwNativeCacheWriter writes a cache exactly as that which would be produced by VW's default cac...
static SHOGUN_BASIC_CLASS CSGObject * __new_CBaggingMachine(EPrimitiveType g)
Definition: class_list.cpp:781
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogPlusOne(EPrimitiveType g)
Definition: class_list.cpp:922
static SHOGUN_BASIC_CLASS CSGObject * __new_COnlineLinearMachine(EPrimitiveType g)
Definition: class_list.cpp:747
static SHOGUN_BASIC_CLASS CSGObject * __new_CIntegration(EPrimitiveType g)
Definition: class_list.cpp:835
static SHOGUN_BASIC_CLASS CSGObject * __new_CMulticlassSOLabels(EPrimitiveType g)
Definition: class_list.cpp:570
static SHOGUN_BASIC_CLASS CSGObject * __new_CLibSVMOneClass(EPrimitiveType g)
Definition: class_list.cpp:584
static SHOGUN_BASIC_CLASS CSGObject * __new_CLogRationalApproximationIndividual(EPrimitiveType g)
Definition: class_list.cpp:848
CSmoothHingeLoss implements the smooth hinge loss function.
The MultitaskKernel allows Multitask Learning via a modified kernel function based on taxonomy...
static SHOGUN_BASIC_CLASS CSGObject * __new_CSNPFeatures(EPrimitiveType g)
static SHOGUN_BASIC_CLASS CSGObject * __new_CDataGenerator(EPrimitiveType g)
class SOBI
Definition: SOBI.h:37
static SHOGUN_BASIC_CLASS CSGObject * __new_CGaussianARDKernel(EPrimitiveType g)
Definition: class_list.cpp:943
static SHOGUN_BASIC_CLASS CSGObject * __new_CMixtureModel(EPrimitiveType g)
Definition: class_list.cpp:820
Kernel Mean Matching.

SHOGUN Machine Learning Toolbox - Documentation