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Perceptron.h
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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) 1999-2009 Soeren Sonnenburg
8  * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
9  */
10 
11 #ifndef _PERCEPTRON_H___
12 #define _PERCEPTRON_H___
13 
14 #include <stdio.h>
15 #include <shogun/lib/common.h>
18 
19 namespace shogun
20 {
31 {
32  public:
33 
36 
38  CPerceptron();
39 
45  CPerceptron(CDotFeatures* traindat, CLabels* trainlab);
46  virtual ~CPerceptron();
47 
53 
55  inline void set_learn_rate(float64_t r)
56  {
57  learn_rate=r;
58  }
59 
61  inline void set_max_iter(int32_t i)
62  {
63  max_iter=i;
64  }
65 
67  void set_initialize_hyperplane(bool initialize_hyperplane);
68 
71 
73  virtual const char* get_name() const { return "Perceptron"; }
74 
75  protected:
84  virtual bool train_machine(CFeatures* data=NULL);
85 
86  protected:
90  int32_t max_iter;
91 
92  private:
97  bool m_initialize_hyperplane;
98 };
99 }
100 #endif
EMachineType
Definition: Machine.h:33
void set_learn_rate(float64_t r)
set learn rate of gradient descent training algorithm
Definition: Perceptron.h:55
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:35
virtual const char * get_name() const
Definition: Perceptron.h:73
bool get_initialize_hyperplane()
get if the hyperplane should be initialized
Definition: Perceptron.cpp:99
Features that support dot products among other operations.
Definition: DotFeatures.h:41
void set_max_iter(int32_t i)
set maximum number of iterations
Definition: Perceptron.h:61
virtual EMachineType get_classifier_type()
Definition: Perceptron.h:52
MACHINE_PROBLEM_TYPE(PT_BINARY)
double float64_t
Definition: common.h:48
void set_initialize_hyperplane(bool initialize_hyperplane)
set if the hyperplane should be initialized
Definition: Perceptron.cpp:94
Class LinearMachine is a generic interface for all kinds of linear machines like classifiers.
Definition: LinearMachine.h:61
Class Perceptron implements the standard linear (online) perceptron.
Definition: Perceptron.h:30
The class Features is the base class of all feature objects.
Definition: Features.h:62
float64_t learn_rate
Definition: Perceptron.h:88
virtual bool train_machine(CFeatures *data=NULL)
Definition: Perceptron.cpp:34
virtual ~CPerceptron()
Definition: Perceptron.cpp:30

SHOGUN Machine Learning Toolbox - Documentation