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QuadraticTimeMMD.h
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3  * Written (w) 2012-2013 Heiko Strathmann
4  * Written (w) 2014 Soumyajit De
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31 
32 #ifndef QUADRATIC_TIME_MMD_H_
33 #define QUADRATIC_TIME_MMD_H_
34 
35 #include <shogun/lib/config.h>
36 
38 
39 namespace shogun
40 {
41 
42 class CFeatures;
43 class CKernel;
44 class CCustomKernel;
45 
48 {
54 };
55 
159 {
160 public:
163 
173  CQuadraticTimeMMD(CKernel* kernel, CFeatures* p_and_q, index_t m);
174 
184  CQuadraticTimeMMD(CKernel* kernel, CFeatures* p, CFeatures* q);
185 
195  CQuadraticTimeMMD(CCustomKernel* custom_kernel, index_t m);
196 
198  virtual ~CQuadraticTimeMMD();
199 
208  virtual float64_t compute_statistic();
209 
217  SGVector<float64_t> compute_statistic(bool multiple_kernels);
218 
228 
236  SGMatrix<float64_t> compute_variance(bool multiple_kernels);
237 
245 
253 
265  virtual float64_t compute_p_value(float64_t statistic);
266 
277  virtual float64_t compute_threshold(float64_t alpha);
278 
280  virtual const char* get_name() const
281  {
282  return "QuadraticTimeMMD";
283  };
284 
287  {
288  return S_QUADRATIC_TIME_MMD;
289  }
290 
319  index_t num_eigenvalues);
320 
363  index_t num_eigenvalues);
364 
371  void set_num_samples_spectrum(index_t num_samples_spectrum);
372 
379  void set_num_eigenvalues_spectrum(index_t num_eigenvalues_spectrum);
380 
382  void set_statistic_type(EQuadraticMMDType statistic_type);
383 
405 
406 protected:
419 
432 
444 
452 
459  float64_t compute_biased_statistic(int m, int n);
460 
467 
468 private:
470  void init();
471 
472 protected:
475 
478 
483 };
484 
485 }
486 
487 #endif /* QUADRATIC_TIME_MMD_H_ */
EQuadraticMMDType m_statistic_type
virtual const char * get_name() const
float64_t compute_variance_under_alternative()
int32_t index_t
Definition: common.h:62
SGVector< float64_t > compute_biased_statistic_variance(int m, int n)
The Custom Kernel allows for custom user provided kernel matrices.
Definition: CustomKernel.h:36
float64_t compute_unbiased_statistic(int m, int n)
virtual float64_t compute_statistic()
void set_statistic_type(EQuadraticMMDType statistic_type)
SGVector< float64_t > fit_null_gamma()
float64_t compute_incomplete_statistic(int n)
Kernel two sample test base class. Provides an interface for performing a two-sample test using a ker...
virtual EStatisticType get_statistic_type() const
SGVector< float64_t > sample_null_spectrum_DEPRECATED(index_t num_samples, index_t num_eigenvalues)
SGVector< float64_t > sample_null_spectrum(index_t num_samples, index_t num_eigenvalues)
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 .
void set_num_eigenvalues_spectrum(index_t num_eigenvalues_spectrum)
double float64_t
Definition: common.h:50
SGVector< float64_t > compute_unbiased_statistic_variance(int m, int n)
void set_num_samples_spectrum(index_t num_samples_spectrum)
virtual float64_t compute_p_value(float64_t statistic)
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
The class Features is the base class of all feature objects.
Definition: Features.h:68
virtual SGVector< float64_t > compute_variance()
The Kernel base class.
Definition: Kernel.h:159
SGVector< float64_t > compute_incomplete_statistic_variance(int n)
virtual float64_t compute_threshold(float64_t alpha)
float64_t compute_biased_statistic(int m, int n)

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