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StreamingMMD.h
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4  * Written (w) 2014 - 2017 Soumyajit De
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31 
32 #ifndef STREAMING_MMD_H_
33 #define STREAMING_MMD_H_
34 
35 #include <utility>
36 #include <memory>
37 #include <functional>
40 
41 namespace shogun
42 {
43 
45 class CKernel;
47 template <typename> class SGVector;
48 template <typename> class SGMatrix;
49 
50 namespace internal
51 {
52 
53 class KernelManager;
54 class MaxTestPower;
55 class MaxCrossValidation;
56 class WeightedMaxTestPower;
57 
58 }
59 
60 class CStreamingMMD : public CMMD
61 {
62  friend class internal::MaxTestPower;
65 public:
66  typedef std::function<float32_t(SGMatrix<float32_t>)> operation;
67 
68  CStreamingMMD();
69  virtual ~CStreamingMMD();
70 
71  virtual float64_t compute_statistic();
72  virtual float64_t compute_variance();
73 
75 
77 
78  void use_gpu(bool gpu);
79  void cleanup();
80 
82  const EStatisticType get_statistic_type() const;
83 
86 
87  void set_num_null_samples(index_t null_samples);
88  const index_t get_num_null_samples() const;
89 
92 
93  virtual const char* get_name() const;
94 protected:
95  virtual const operation get_direct_estimation_method() const=0;
96  virtual float64_t normalize_statistic(float64_t statistic) const=0;
97  virtual const float64_t normalize_variance(float64_t variance) const=0;
98  bool use_gpu() const;
99  std::shared_ptr<CKernelSelectionStrategy> get_strategy();
100 private:
101  struct Self;
102  std::unique_ptr<Self> self;
103  virtual std::pair<float64_t, float64_t> compute_statistic_variance();
104  std::pair<SGVector<float64_t>, SGMatrix<float64_t> > compute_statistic_and_Q(const internal::KernelManager&);
105 };
106 
107 }
108 #endif // STREAMING_MMD_H_
const ENullApproximationMethod get_null_approximation_method() const
void set_statistic_type(EStatisticType stype)
virtual const char * get_name() const
void set_variance_estimation_method(EVarianceEstimationMethod vmethod)
virtual SGVector< float64_t > compute_multiple()
int32_t index_t
Definition: common.h:72
const index_t get_num_null_samples() const
virtual float64_t compute_variance()
const EStatisticType get_statistic_type() const
const EVarianceEstimationMethod get_variance_estimation_method() const
std::shared_ptr< CKernelSelectionStrategy > get_strategy()
virtual SGVector< float64_t > sample_null()
virtual const operation get_direct_estimation_method() const =0
double float64_t
Definition: common.h:60
void set_null_approximation_method(ENullApproximationMethod nmethod)
friend class internal::WeightedMaxTestPower
Definition: StreamingMMD.h:63
virtual const float64_t normalize_variance(float64_t variance) const =0
EStatisticType
Definition: TestEnums.h:40
EVarianceEstimationMethod
Definition: TestEnums.h:47
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
virtual float64_t normalize_statistic(float64_t statistic) const =0
std::function< float32_t(SGMatrix< float32_t >)> operation
Definition: StreamingMMD.h:66
Abstract base class that provides an interface for performing kernel two-sample test using Maximum Me...
Definition: MMD.h:120
void set_num_null_samples(index_t null_samples)
friend class internal::MaxCrossValidation
Definition: StreamingMMD.h:64
friend class internal::MaxTestPower
Definition: StreamingMMD.h:62
virtual float64_t compute_statistic()
ENullApproximationMethod
Definition: TestEnums.h:53

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