10 #ifndef __LINEARTIMEMMD_H_ 11 #define __LINEARTIMEMMD_H_ 15 #include <shogun/lib/external/libqp.h> 20 class CStreamingFeatures;
189 bool multiple_kernels=
false);
244 return "LinearTimeMMD";
void set_blocksize(index_t blocksize)
CStreamingFeatures * m_streaming_p
virtual const char * get_name() const
virtual void compute_statistic_and_Q(SGVector< float64_t > &statistic, SGMatrix< float64_t > &Q)
virtual CFeatures * get_p_and_q()
void set_simulate_h0(bool simulate_h0)
virtual void compute_statistic_and_variance(SGVector< float64_t > &statistic, SGVector< float64_t > &variance, bool multiple_kernels=false)
virtual ~CLinearTimeMMD()
virtual float64_t compute_threshold(float64_t alpha)
virtual EStatisticType get_statistic_type() const
CStreamingFeatures * m_streaming_q
virtual float64_t perform_test()
virtual void set_p_and_q(CFeatures *p_and_q)
all of classes and functions are contained in the shogun namespace
virtual float64_t compute_variance_estimate()
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.
Streaming features are features which are used for online algorithms.
This class implements the linear time Maximum Mean Statistic as described in [1]. This statistic is i...
virtual CStreamingFeatures * get_streaming_q()
virtual CStreamingFeatures * get_streaming_p()
virtual SGVector< float64_t > bootstrap_null()
virtual float64_t compute_p_value(float64_t statistic)
virtual float64_t compute_statistic()