10 #ifndef __QUADRACTIMEMMD_H_
11 #define __QUADRACTIMEMMD_H_
173 return "QuadraticTimeMMD";
207 #endif // HAVE_LAPACK
index_t m_num_samples_spectrum
EQuadraticMMDType m_statistic_type
virtual const char * get_name() const
virtual ~CQuadraticTimeMMD()
The Custom Kernel allows for custom user provided kernel matrices.
virtual float64_t compute_statistic()
void set_statistic_type(EQuadraticMMDType statistic_type)
SGVector< float64_t > fit_null_gamma()
index_t m_num_eigenvalues_spectrum
virtual EStatisticType get_statistic_type() const
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 .
void set_num_eigenvalues_spectrum(index_t num_eigenvalues_spectrum)
virtual float64_t compute_unbiased_statistic()
void set_num_samples_sepctrum(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
Two sample test base class. Provides an interface for performing a two-sample test, i.e. Given samples from two distributions and , the null-hypothesis is: , the alternative hypothesis: .
The class Features is the base class of all feature objects.
virtual float64_t compute_biased_statistic()
virtual float64_t compute_threshold(float64_t alpha)