32 #ifndef STREAMING_MMD_H_ 33 #define STREAMING_MMD_H_ 47 template <
typename>
class SGVector;
48 template <
typename>
class SGMatrix;
55 class MaxCrossValidation;
56 class WeightedMaxTestPower;
66 typedef std::function<float32_t(SGMatrix<float32_t>)>
operation;
93 virtual const char*
get_name()
const;
99 std::shared_ptr<CKernelSelectionStrategy>
get_strategy();
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&);
108 #endif // STREAMING_MMD_H_ void set_statistic_type(EStatisticType stype)
void set_variance_estimation_method(EVarianceEstimationMethod vmethod)
virtual SGVector< float64_t > compute_multiple()
virtual float64_t compute_variance()
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
void set_null_approximation_method(ENullApproximationMethod nmethod)
friend class internal::WeightedMaxTestPower
virtual const float64_t normalize_variance(float64_t variance) const =0
const index_t get_num_null_samples() const
const EStatisticType get_statistic_type() const
EVarianceEstimationMethod
all of classes and functions are contained in the shogun namespace
virtual float64_t normalize_statistic(float64_t statistic) const =0
std::function< float32_t(SGMatrix< float32_t >)> operation
const ENullApproximationMethod get_null_approximation_method() const
Abstract base class that provides an interface for performing kernel two-sample test using Maximum Me...
void set_num_null_samples(index_t null_samples)
friend class internal::MaxCrossValidation
friend class internal::MaxTestPower
virtual float64_t compute_statistic()
virtual const char * get_name() const