30 #ifndef _MIXTUREMODEL_H__
31 #define _MIXTUREMODEL_H__
62 virtual const char*
get_name()
const {
return "MixtureModel"; }
SGVector< float64_t > cluster(SGVector< float64_t > point)
void set_convergence_tolerance(float64_t epsilon)
bool train(CFeatures *data=NULL)
Base class Distribution from which all methods implementing a distribution are derived.
virtual float64_t get_log_derivative(int32_t num_param, int32_t num_example)
virtual const char * get_name() const
virtual float64_t get_log_likelihood_example(int32_t num_example)
int32_t get_num_model_parameters()
index_t get_num_components() const
Dynamic array class for CSGObject pointers that creates an array that can be used like a list or an a...
CDistribution * get_component(index_t index) const
SGVector< float64_t > sample()
all of classes and functions are contained in the shogun namespace
int32_t get_max_iters() const
void set_max_iters(int32_t max_iters)
The class Features is the base class of all feature objects.
CDynamicObjectArray * get_components() const
float64_t get_log_model_parameter(int32_t num_param=1)
float64_t get_convergence_tolerance() const
void set_components(CDynamicObjectArray *components)
SGVector< float64_t > get_weights() const
void set_weights(SGVector< float64_t > weights)
This is the generic class for mixture models. The final distribution is a mixture of various simple d...