| build_gradient_parameter_dictionary(CMap< TParameter *, CSGObject * > *dict) | CSGObject | |
| CGaussianLikelihood() | CGaussianLikelihood | |
| CGaussianLikelihood(float64_t sigma) | CGaussianLikelihood | |
| CLikelihoodModel() | CLikelihoodModel | |
| clone() | CSGObject | virtual |
| CSGObject() | CSGObject | |
| CSGObject(const CSGObject &orig) | CSGObject | |
| deep_copy() const | CSGObject | virtual |
| equals(CSGObject *other, float64_t accuracy=0.0, bool tolerant=false) | CSGObject | virtual |
| get_first_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const | CGaussianLikelihood | virtual |
| get_first_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const | CGaussianLikelihood | virtual |
| get_first_moments(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab) const | CLikelihoodModel | virtual |
| get_global_io() | CSGObject | |
| get_global_parallel() | CSGObject | |
| get_global_version() | CSGObject | |
| get_log_probability_derivative_f(const CLabels *lab, SGVector< float64_t > func, index_t i) const | CGaussianLikelihood | virtual |
| get_log_probability_f(const CLabels *lab, SGVector< float64_t > func) const | CGaussianLikelihood | virtual |
| get_log_probability_fmatrix(const CLabels *lab, SGMatrix< float64_t > F) const | CLikelihoodModel | virtual |
| get_log_zeroth_moments(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab) const | CGaussianLikelihood | virtual |
| get_model_type() const | CGaussianLikelihood | virtual |
| get_modelsel_names() | CSGObject | |
| get_modsel_param_descr(const char *param_name) | CSGObject | |
| get_modsel_param_index(const char *param_name) | CSGObject | |
| get_name() const | CGaussianLikelihood | virtual |
| get_predictive_log_probabilities(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) | CLikelihoodModel | virtual |
| get_predictive_means(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const | CGaussianLikelihood | virtual |
| get_predictive_variances(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const | CGaussianLikelihood | virtual |
| get_second_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const | CGaussianLikelihood | virtual |
| get_second_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const | CGaussianLikelihood | virtual |
| get_second_moments(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab) const | CLikelihoodModel | virtual |
| get_sigma() | CGaussianLikelihood | |
| get_third_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const | CGaussianLikelihood | virtual |
| io | CSGObject | |
| is_generic(EPrimitiveType *generic) const | CSGObject | virtual |
| load_serializable(CSerializableFile *file, const char *prefix="") | CSGObject | virtual |
| load_serializable_post() | CSGObject | protectedvirtual |
| load_serializable_pre() | CSGObject | protectedvirtual |
| m_gradient_parameters | CSGObject | |
| m_hash | CSGObject | |
| m_model_selection_parameters | CSGObject | |
| m_parameters | CSGObject | |
| obtain_from_generic(CLikelihoodModel *lik) | CGaussianLikelihood | static |
| parallel | CSGObject | |
| parameter_hash_changed() | CSGObject | virtual |
| print_modsel_params() | CSGObject | |
| print_serializable(const char *prefix="") | CSGObject | virtual |
| save_serializable(CSerializableFile *file, const char *prefix="") | CSGObject | virtual |
| save_serializable_post() | CSGObject | protectedvirtual |
| save_serializable_pre() | CSGObject | protectedvirtual |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_generic() | CSGObject | |
| set_global_io(SGIO *io) | CSGObject | |
| set_global_parallel(Parallel *parallel) | CSGObject | |
| set_global_version(Version *version) | CSGObject | |
| set_sigma(float64_t sigma) | CGaussianLikelihood | |
| shallow_copy() const | CSGObject | virtual |
| supports_binary() const | CLikelihoodModel | virtual |
| supports_multiclass() const | CLikelihoodModel | virtual |
| supports_regression() const | CGaussianLikelihood | virtual |
| unset_generic() | CSGObject | |
| update_parameter_hash() | CSGObject | virtual |
| version | CSGObject | |
| ~CGaussianLikelihood() | CGaussianLikelihood | virtual |
| ~CLikelihoodModel() | CLikelihoodModel | virtual |
| ~CSGObject() | CSGObject | virtual |
