41 #ifndef _SOFTMAXLIKELIHOOD_H_ 42 #define _SOFTMAXLIKELIHOOD_H_ 44 #include <shogun/lib/config.h> 92 virtual const char*
get_name()
const {
return "SoftMaxLikelihood"; }
virtual void set_num_samples(index_t num_samples)
Class that models Soft-Max likelihood.
virtual float64_t get_first_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const
The class Labels models labels, i.e. class assignments of objects.
virtual SGVector< float64_t > get_predictive_variances(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const
virtual SGVector< float64_t > get_log_zeroth_moments(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab) const
virtual const char * get_name() const
std::enable_if<!std::is_same< T, complex128_t >::value, float64_t >::type mean(const Container< T > &a)
virtual SGVector< float64_t > get_predictive_means(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const
virtual ~CSoftMaxLikelihood()
virtual SGVector< float64_t > get_log_probability_f(const CLabels *lab, SGVector< float64_t > func) const
virtual SGVector< float64_t > get_log_probability_derivative_f(const CLabels *lab, SGVector< float64_t > func, index_t i) const
virtual SGVector< float64_t > get_predictive_log_probabilities(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL)
all of classes and functions are contained in the shogun namespace
virtual bool supports_multiclass() const
The Likelihood model base class.
virtual float64_t get_second_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const