| FCNN4R-package | Fast Compressed Neural Networks for R |
| is.mlp_net | Is it an object of 'mlp_net' class? |
| mlp_eval | Evaluation |
| mlp_expand_reorder_inputs | Manipulating network inputs |
| mlp_export_C | Export multilayer perceptron network to a C function |
| mlp_export_fcnn | Export and import multilayer perceptron network to/from a text file in FCNN format |
| mlp_get_layers | General information about network |
| mlp_get_name | Get and set network names |
| mlp_get_no_active_w | General information about network |
| mlp_get_no_w | General information about network |
| mlp_get_w | Setting and retrieving status (on/off) and value of individual weight(s) |
| mlp_get_weights | Set and retrieve (active) weights' values |
| mlp_get_w_abs_idx | Retrieving absolute weight index |
| mlp_get_w_idx | Retrieving absolute weight index |
| mlp_get_w_st | Setting and retrieving status (on/off) and value of individual weight(s) |
| mlp_grad | Computing mean squared error, its gradient, and output derivatives |
| mlp_gradi | Computing mean squared error, its gradient, and output derivatives |
| mlp_gradij | Computing mean squared error, its gradient, and output derivatives |
| mlp_import_fcnn | Export and import multilayer perceptron network to/from a text file in FCNN format |
| mlp_jacob | Computing mean squared error, its gradient, and output derivatives |
| mlp_merge | Combining two networks into one |
| mlp_mse | Computing mean squared error, its gradient, and output derivatives |
| mlp_net | Create objects of 'mlp_net' class |
| mlp_net-absolute-weight-indices | Retrieving absolute weight index |
| mlp_net-accessing-individual-weights | Setting and retrieving status (on/off) and value of individual weight(s) |
| mlp_net-class | An S4 class representing Multilayer Perception Network. |
| mlp_net-combining-two-networks | Combining two networks into one |
| mlp_net-display | Displaying networks (objects of 'mlp_net' class) |
| mlp_net-export-import | Export and import multilayer perceptron network to/from a text file in FCNN format |
| mlp_net-general-information | General information about network |
| mlp_net-manipulating-network-inputs | Manipulating network inputs |
| mlp_net-method | An S4 class representing Multilayer Perception Network. |
| mlp_net-MSE-gradients | Computing mean squared error, its gradient, and output derivatives |
| mlp_net-names | Get and set network names |
| mlp_net-weights-access | Set and retrieve (active) weights' values |
| mlp_plot | Plotting multilayer perceptron network |
| mlp_prune_mag | Minimum magnitude pruning |
| mlp_prune_obs | Optimal Brain Surgeon pruning |
| mlp_rm_input_neurons | Manipulating network inputs |
| mlp_rm_neurons | Remove redundant neurons in a multilayer perceptron network |
| mlp_rnd_weights | This function sets network weights to random values drawn from uniform distribution. |
| mlp_set_activation | Set network activation functions |
| mlp_set_name | Get and set network names |
| mlp_set_w | Setting and retrieving status (on/off) and value of individual weight(s) |
| mlp_set_weights | Set and retrieve (active) weights' values |
| mlp_set_w_st | Setting and retrieving status (on/off) and value of individual weight(s) |
| mlp_stack | Combining two networks into one |
| mlp_teach_bp | Backpropagation (batch) teaching |
| mlp_teach_grprop | Rprop teaching - minimising arbitrary objective function |
| mlp_teach_rprop | Rprop teaching |
| mlp_teach_sa | Teaching networks using Simulated Annealing |
| mlp_teach_sgd | Stochastic gradient descent with (optional) RMS weights scaling, weight decay, and momentum |
| print-method | Displaying networks (objects of 'mlp_net' class) |
| read-write-fcnndataset | Reading and writing datasets in the FCNN format |
| read.fcnndataset | Reading and writing datasets in the FCNN format |
| show-method | Displaying networks (objects of 'mlp_net' class) |
| summary-method | Displaying networks (objects of 'mlp_net' class) |
| write.fcnndataset | Reading and writing datasets in the FCNN format |