95 int32_t num_param, int32_t num_example);
224 virtual const char*
get_name()
const {
return "Gaussian"; }
228 void register_params();
250 #endif //_GAUSSIAN_H__
SGVector< float64_t > sample()
void set_u(SGMatrix< float64_t > u)
Gaussian distribution interface.
virtual bool train(CFeatures *data=NULL)
virtual float64_t compute_log_PDF(SGVector< float64_t > point)
Base class Distribution from which all methods implementing a distribution are derived.
virtual float64_t compute_PDF(SGVector< float64_t > point)
virtual float64_t update_params_em(float64_t *alpha_k, int32_t len)
SGMatrix< float64_t > m_u
virtual SGVector< float64_t > get_mean()
virtual float64_t get_log_model_parameter(int32_t num_param)
SGMatrix< float64_t > get_u()
static CGaussian * obtain_from_generic(CDistribution *distribution)
virtual void set_cov(SGMatrix< float64_t > cov)
SGVector< float64_t > m_mean
virtual SGMatrix< float64_t > get_cov()
void set_cov_type(ECovType cov_type)
virtual float64_t get_log_likelihood_example(int32_t num_example)
virtual const char * get_name() const
all of classes and functions are contained in the shogun namespace
The class Features is the base class of all feature objects.
static float64_t exp(float64_t x)
SGVector< float64_t > get_d()
virtual void set_mean(const SGVector< float64_t > mean)
virtual int32_t get_num_model_parameters()
virtual float64_t get_log_derivative(int32_t num_param, int32_t num_example)
void set_d(const SGVector< float64_t > d)
SGVector< float64_t > m_d