SHOGUN  6.0.0
MaxMeasure.cpp
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3  * Written (W) 2012 - 2013 Heiko Strathmann
4  * Written (w) 2014 - 2017 Soumyajit De
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31 
32 #include <algorithm>
33 #include <shogun/lib/SGVector.h>
34 #include <shogun/lib/SGMatrix.h>
35 #include <shogun/kernel/Kernel.h>
41 
42 using namespace shogun;
43 using namespace internal;
44 
45 MaxMeasure::MaxMeasure(KernelManager& km, CMMD* est) : KernelSelection(km, est)
46 {
47 }
48 
49 MaxMeasure::~MaxMeasure()
50 {
51 }
52 
53 SGVector<float64_t> MaxMeasure::get_measure_vector()
54 {
55  return measures;
56 }
57 
58 SGMatrix<float64_t> MaxMeasure::get_measure_matrix()
59 {
61  return SGMatrix<float64_t>();
62 }
63 
64 void MaxMeasure::init_measures()
65 {
66  const index_t num_kernels=kernel_mgr.num_kernels();
67  REQUIRE(num_kernels>0, "Number of kernels is %d!\n", kernel_mgr.num_kernels());
68  if (measures.size()!=num_kernels)
69  measures=SGVector<float64_t>(num_kernels);
70  std::fill(measures.data(), measures.data()+measures.size(), 0);
71 }
72 
73 void MaxMeasure::compute_measures()
74 {
75  REQUIRE(estimator!=nullptr, "Estimator is not set!\n");
76  CQuadraticTimeMMD* mmd=dynamic_cast<CQuadraticTimeMMD*>(estimator);
77  if (mmd!=nullptr && kernel_mgr.same_distance_type())
78  measures=mmd->multikernel()->statistic(kernel_mgr);
79  else
80  {
81  init_measures();
82  auto existing_kernel=estimator->get_kernel();
83  const auto num_kernels=kernel_mgr.num_kernels();
84  for (auto i=0; i<num_kernels; ++i)
85  {
86  auto kernel=kernel_mgr.kernel_at(i);
87  estimator->set_kernel(kernel);
88  measures[i]=estimator->compute_statistic();
89  estimator->cleanup();
90  }
91  if (existing_kernel)
92  estimator->set_kernel(existing_kernel);
93  }
94 }
95 
96 CKernel* MaxMeasure::select_kernel()
97 {
98  compute_measures();
99  ASSERT(measures.size()==kernel_mgr.num_kernels());
100  auto max_element=std::max_element(measures.vector, measures.vector+measures.vlen);
101  auto max_idx=std::distance(measures.vector, max_element);
102  SG_SDEBUG("Selected kernel at %d position!\n", max_idx);
103  return kernel_mgr.kernel_at(max_idx);
104 }
float distance(CJLCoverTreePoint p1, CJLCoverTreePoint p2, float64_t upper_bound)
int32_t index_t
Definition: common.h:72
#define REQUIRE(x,...)
Definition: SGIO.h:205
#define SG_SNOTIMPLEMENTED
Definition: SGIO.h:197
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 .
#define ASSERT(x)
Definition: SGIO.h:200
CMultiKernelQuadraticTimeMMD * multikernel()
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
#define SG_SDEBUG(...)
Definition: SGIO.h:167
Abstract base class that provides an interface for performing kernel two-sample test using Maximum Me...
Definition: MMD.h:120
The Kernel base class.

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