FCNN4R-package          Fast Compressed Neural Networks for R
is.mlp_net              Is it an object of 'mlp_net' class?
mlp_eval                Evaluation
mlp_export_C            Export multilayer perceptron network to a C
                        function
mlp_net                 Create objects of 'mlp_net' class
mlp_net-MSE-gradients   Computing mean squared error, its gradient, and
                        output derivatives
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-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_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_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
read-write-fcnndataset
                        Reading and writing datasets in the FCNN format
