Table of Contents - t_learn-0.1.1.8 Documentation
Pages
Classes and Modules
- TLearn
- TLearn::EM_Gaussian
- TLearn::FNN
- TLearn::FNN::Node
- TLearn::HopFieldNet
- TLearn::K_Means
- TLearn::K_Means::Cluster
Methods
- ::add_noise_data — TLearn
- ::evaluate — TLearn
- ::new — TLearn::FNN
- ::new — TLearn::FNN::Node
- ::new — TLearn::HopFieldNet
- ::new — TLearn::K_Means::Cluster
- #add_layer — TLearn::FNN
- #add_v — TLearn::K_Means::Cluster
- #back_propagation — TLearn::FNN
- #calc_ave — TLearn::EM_Gaussian
- #calc_ave_err — TLearn::FNN
- #calc_center — TLearn::K_Means::Cluster
- #calc_connected_factor — TLearn::HopFieldNet
- #calc_conv — TLearn::EM_Gaussian
- #calc_delta — TLearn::FNN
- #calc_dist — TLearn::K_Means
- #calc_err — TLearn::FNN
- #calc_first_ave_std — TLearn::EM_Gaussian
- #calc_log_likelihood — TLearn::EM_Gaussian
- #change_center? — TLearn::K_Means::Cluster
- #change_clusters_center? — TLearn::K_Means
- #connect_nodes — TLearn::FNN
- #create_log — TLearn::EM_Gaussian
- #e_step — TLearn::EM_Gaussian
- #energy — TLearn::HopFieldNet
- #evaluate — TLearn::FNN
- #fit — TLearn::EM_Gaussian
- #fit — TLearn::FNN
- #fit — TLearn::K_Means
- #format_for_log — TLearn::K_Means
- #format_hash — TLearn::K_Means::Cluster
- #gauusian — TLearn::EM_Gaussian
- #gauusian_over_2dim — TLearn::EM_Gaussian
- #get_output_layer — TLearn::FNN
- #ini_ave — TLearn::EM_Gaussian
- #ini_conv — TLearn::EM_Gaussian
- #init — TLearn::EM_Gaussian
- #init — TLearn::K_Means
- #input — TLearn::FNN::Node
- #load_train_data — TLearn::HopFieldNet
- #m_step — TLearn::EM_Gaussian
- #make_array — TLearn::EM_Gaussian
- #memorize — TLearn::HopFieldNet
- #propagation — TLearn::FNN
- #remember — TLearn::HopFieldNet
- #reset_v_list — TLearn::K_Means::Cluster
- #scale — TLearn::EM_Gaussian
- #set_id — TLearn::FNN::Node
- #sigmoid_fun — TLearn::FNN::Node
- #update_external_w — TLearn::HopFieldNet
- #update_w — TLearn::FNN::Node