60 log_likelihood+=normalize;
67 return log_likelihood;
84 sum_weights+=weight_j;
This is the base class for Expectation Maximization (EM). EM for various purposes can be derived from...
SGVector< float64_t > weights
static CDistribution * obtain_from_generic(CSGObject *object)
SGMatrix< float64_t > alpha
CDynamicObjectArray * components
Base class Distribution from which all methods implementing a distribution are derived.
virtual float64_t update_params_em(float64_t *alpha_k, int32_t len)
static T log_sum_exp(SGVector< T > values)
all of classes and functions are contained in the shogun namespace
virtual ~CEMMixtureModel()
This structure is used for storing data required for using the generic Expectation Maximization (EM) ...
static float64_t exp(float64_t x)
static float64_t log(float64_t v)
CSGObject * get_element(int32_t index) const
virtual float64_t expectation_step()
virtual float64_t get_log_likelihood_example(int32_t num_example)=0
virtual void maximization_step()