18 using namespace shogun;
49 SG_ERROR(
"Expected features of class string type word\n")
58 for (i=0; i< (int32_t) (1<<16); i++)
67 get_feature_vector(vec, len, free_vec);
69 for (feat=0; feat<len ; feat++)
73 free_feature_vector(vector, vec, free_vec);
76 for (i=0; i< (int32_t) (1<<16); i++)
93 get_feature_vector(num_example, len, free_vec);
95 for (int32_t i=0; i<len; i++)
96 loglik+=
hist[vector[i]];
99 free_feature_vector(vector, num_example, free_vec);
119 get_feature_vector(num_example, len, free_vec);
121 int32_t num_occurences=0;
123 for (int32_t i=0; i<len; i++)
125 deriv+=
hist[vector[i]];
127 if (vector[i]==num_param)
132 free_feature_vector(vector, num_example, free_vec);
134 if (num_occurences>0)
145 return hist[num_param];
154 for (int32_t i=0; i<histogram.
vlen; i++)
virtual void set_features(CFeatures *f)
static const float64_t INFTY
infinity
virtual bool set_histogram(const SGVector< float64_t > histogram)
virtual int32_t get_num_vectors() const =0
Base class Distribution from which all methods implementing a distribution are derived.
virtual SGVector< float64_t > get_histogram()
static const float64_t ALMOST_NEG_INFTY
almost neg (log) infinity
virtual EFeatureClass get_feature_class() const =0
virtual float64_t get_log_model_parameter(int32_t num_param)
virtual bool train(CFeatures *data=NULL)
The class Features is the base class of all feature objects.
static float64_t log(float64_t v)
virtual float64_t get_log_likelihood_example(int32_t num_example)
virtual int32_t get_num_model_parameters()
virtual float64_t get_log_derivative(int32_t num_param, int32_t num_example)
virtual EFeatureType get_feature_type() const =0