| apply(CFeatures *data=NULL) | CMachine | virtual |
| apply_binary(CFeatures *data) | CNeuralNetwork | virtual |
| apply_latent(CFeatures *data=NULL) | CMachine | virtual |
| apply_locked(SGVector< index_t > indices) | CMachine | virtual |
| apply_locked_binary(SGVector< index_t > indices) | CMachine | virtual |
| apply_locked_latent(SGVector< index_t > indices) | CMachine | virtual |
| apply_locked_multiclass(SGVector< index_t > indices) | CMachine | virtual |
| apply_locked_regression(SGVector< index_t > indices) | CMachine | virtual |
| apply_locked_structured(SGVector< index_t > indices) | CMachine | virtual |
| apply_multiclass(CFeatures *data) | CNeuralNetwork | virtual |
| apply_one(int32_t i) | CMachine | virtual |
| apply_regression(CFeatures *data) | CNeuralNetwork | virtual |
| apply_structured(CFeatures *data=NULL) | CMachine | virtual |
| build_gradient_parameter_dictionary(CMap< TParameter *, CSGObject * > *dict) | CSGObject | |
| CDeepBeliefNetwork class | CNeuralNetwork | friend |
| check_gradients(float64_t approx_epsilon=1.0e-3, float64_t s=1.0e-9) | CNeuralNetwork | virtual |
| clone() | CSGObject | virtual |
| CMachine() | CMachine | |
| CNeuralNetwork() | CNeuralNetwork | |
| CNeuralNetwork(CDynamicObjectArray *layers) | CNeuralNetwork | |
| compute_error(SGMatrix< float64_t > inputs, SGMatrix< float64_t > targets) | CNeuralNetwork | protectedvirtual |
| compute_error(SGMatrix< float64_t > targets) | CNeuralNetwork | protectedvirtual |
| compute_gradients(SGMatrix< float64_t > inputs, SGMatrix< float64_t > targets, SGVector< float64_t > gradients) | CNeuralNetwork | protectedvirtual |
| connect(int32_t i, int32_t j) | CNeuralNetwork | virtual |
| CSGObject() | CSGObject | |
| CSGObject(const CSGObject &orig) | CSGObject | |
| data_lock(CLabels *labs, CFeatures *features) | CMachine | virtual |
| data_unlock() | CMachine | virtual |
| deep_copy() const | CSGObject | virtual |
| disconnect(int32_t i, int32_t j) | CNeuralNetwork | virtual |
| disconnect_all() | CNeuralNetwork | virtual |
| equals(CSGObject *other, float64_t accuracy=0.0, bool tolerant=false) | CSGObject | virtual |
| features_to_matrix(CFeatures *features) | CNeuralNetwork | protected |
| forward_propagate(CFeatures *data, int32_t j=-1) | CNeuralNetwork | protectedvirtual |
| forward_propagate(SGMatrix< float64_t > inputs, int32_t j=-1) | CNeuralNetwork | protectedvirtual |
| get(const Tag< T > &_tag) const | CSGObject | |
| get(const std::string &name) const | CSGObject | |
| get_classifier_type() | CNeuralNetwork | virtual |
| get_dropout_hidden() const | CNeuralNetwork | |
| get_dropout_input() const | CNeuralNetwork | |
| get_epsilon() const | CNeuralNetwork | |
| get_gd_error_damping_coeff() const | CNeuralNetwork | |
| get_gd_learning_rate() const | CNeuralNetwork | |
| get_gd_learning_rate_decay() const | CNeuralNetwork | |
| get_gd_mini_batch_size() const | CNeuralNetwork | |
| get_gd_momentum() const | CNeuralNetwork | |
| get_global_io() | CSGObject | |
| get_global_parallel() | CSGObject | |
| get_global_version() | CSGObject | |
| get_l1_coefficient() const | CNeuralNetwork | |
| get_l2_coefficient() const | CNeuralNetwork | |
| get_labels() | CMachine | virtual |
| get_layer(int32_t i) | CNeuralNetwork | protected |
| get_layer_parameters(int32_t i) | CNeuralNetwork | |
| get_layers() | CNeuralNetwork | |
| get_machine_problem_type() const | CNeuralNetwork | virtual |
| get_max_norm() const | CNeuralNetwork | |
| get_max_num_epochs() const | CNeuralNetwork | |
| get_max_train_time() | CMachine | |
| 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 | CNeuralNetwork | virtual |
| get_num_inputs() | CNeuralNetwork | |
| get_num_outputs() | CNeuralNetwork | |
| get_num_parameters() | CNeuralNetwork | |
| get_optimization_method() const | CNeuralNetwork | |
| get_parameters() | CNeuralNetwork | |
| get_solver_type() | CMachine | |
| has(const std::string &name) const | CSGObject | |
| has(const Tag< T > &tag) const | CSGObject | |
| has(const std::string &name) const | CSGObject | |
| initialize_neural_network(float64_t sigma=0.01f) | CNeuralNetwork | virtual |
| io | CSGObject | |
| is_data_locked() const | CMachine | |
| is_generic(EPrimitiveType *generic) const | CSGObject | virtual |
| is_label_valid(CLabels *lab) const | CNeuralNetwork | protectedvirtual |
| labels_to_matrix(CLabels *labs) | CNeuralNetwork | protected |
| load_serializable(CSerializableFile *file, const char *prefix="") | CSGObject | virtual |
| load_serializable_post() | CSGObject | protectedvirtual |
| load_serializable_pre() | CSGObject | protectedvirtual |
| m_adj_matrix | CNeuralNetwork | protected |
| m_batch_size | CNeuralNetwork | protected |
| m_data_locked | CMachine | protected |
| m_dropout_hidden | CNeuralNetwork | protected |
| m_dropout_input | CNeuralNetwork | protected |
| m_epsilon | CNeuralNetwork | protected |
| m_gd_error_damping_coeff | CNeuralNetwork | protected |
| m_gd_learning_rate | CNeuralNetwork | protected |
| m_gd_learning_rate_decay | CNeuralNetwork | protected |
| m_gd_mini_batch_size | CNeuralNetwork | protected |
| m_gd_momentum | CNeuralNetwork | protected |
| m_gradient_parameters | CSGObject | |
| m_hash | CSGObject | |
| m_index_offsets | CNeuralNetwork | protected |
| m_is_training | CNeuralNetwork | protected |
| m_l1_coefficient | CNeuralNetwork | protected |
| m_l2_coefficient | CNeuralNetwork | protected |
| m_labels | CMachine | protected |
| m_layers | CNeuralNetwork | protected |
| m_max_norm | CNeuralNetwork | protected |
| m_max_num_epochs | CNeuralNetwork | protected |
| m_max_train_time | CMachine | protected |
| m_model_selection_parameters | CSGObject | |
| m_num_inputs | CNeuralNetwork | protected |
| m_num_layers | CNeuralNetwork | protected |
| m_optimization_method | CNeuralNetwork | protected |
| m_param_regularizable | CNeuralNetwork | protected |
| m_parameters | CSGObject | |
| m_params | CNeuralNetwork | protected |
| m_solver_type | CMachine | protected |
| m_store_model_features | CMachine | protected |
| m_total_num_parameters | CNeuralNetwork | protected |
| parallel | CSGObject | |
| parameter_hash_changed() | CSGObject | virtual |
| post_lock(CLabels *labs, CFeatures *features) | CMachine | virtual |
| print_modsel_params() | CSGObject | |
| print_serializable(const char *prefix="") | CSGObject | virtual |
| quick_connect() | CNeuralNetwork | virtual |
| register_param(Tag< T > &_tag, const T &value) | CSGObject | protected |
| register_param(const std::string &name, const T &value) | CSGObject | protected |
| save_serializable(CSerializableFile *file, const char *prefix="") | CSGObject | virtual |
| save_serializable_post() | CSGObject | protectedvirtual |
| save_serializable_pre() | CSGObject | protectedvirtual |
| set(const Tag< T > &_tag, const T &value) | CSGObject | |
| set(const std::string &name, const T &value) | CSGObject | |
| set_batch_size(int32_t batch_size) | CNeuralNetwork | protectedvirtual |
| set_dropout_hidden(float64_t dropout_hidden) | CNeuralNetwork | |
| set_dropout_input(float64_t dropout_input) | CNeuralNetwork | |
| set_epsilon(float64_t epsilon) | CNeuralNetwork | |
| set_gd_error_damping_coeff(float64_t gd_error_damping_coeff) | CNeuralNetwork | |
| set_gd_learning_rate(float64_t gd_learning_rate) | CNeuralNetwork | |
| set_gd_learning_rate_decay(float64_t gd_learning_rate_decay) | CNeuralNetwork | |
| set_gd_mini_batch_size(int32_t gd_mini_batch_size) | CNeuralNetwork | |
| set_gd_momentum(float64_t gd_momentum) | CNeuralNetwork | |
| 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_l1_coefficient(float64_t l1_coefficient) | CNeuralNetwork | |
| set_l2_coefficient(float64_t l2_coefficient) | CNeuralNetwork | |
| set_labels(CLabels *lab) | CNeuralNetwork | virtual |
| set_layers(CDynamicObjectArray *layers) | CNeuralNetwork | virtual |
| set_max_norm(float64_t max_norm) | CNeuralNetwork | |
| set_max_num_epochs(int32_t max_num_epochs) | CNeuralNetwork | |
| set_max_train_time(float64_t t) | CMachine | |
| set_optimization_method(ENNOptimizationMethod optimization_method) | CNeuralNetwork | |
| set_solver_type(ESolverType st) | CMachine | |
| set_store_model_features(bool store_model) | CMachine | virtual |
| shallow_copy() const | CSGObject | virtual |
| store_model_features() | CMachine | protectedvirtual |
| supports_locking() const | CMachine | virtual |
| train(CFeatures *data=NULL) | CMachine | virtual |
| train_gradient_descent(SGMatrix< float64_t > inputs, SGMatrix< float64_t > targets) | CNeuralNetwork | protectedvirtual |
| train_lbfgs(SGMatrix< float64_t > inputs, SGMatrix< float64_t > targets) | CNeuralNetwork | protectedvirtual |
| train_locked(SGVector< index_t > indices) | CMachine | virtual |
| train_machine(CFeatures *data=NULL) | CNeuralNetwork | protectedvirtual |
| train_require_labels() const | CMachine | protectedvirtual |
| transform(CDenseFeatures< float64_t > *data) | CNeuralNetwork | virtual |
| unset_generic() | CSGObject | |
| update_parameter_hash() | CSGObject | virtual |
| version | CSGObject | |
| ~CMachine() | CMachine | virtual |
| ~CNeuralNetwork() | CNeuralNetwork | virtual |
| ~CSGObject() | CSGObject | virtual |
