A MORE flexible neural network package

[Package List] [Top]

Documentation for package `AMORE' version 0.1.1

Help Pages

adapt.C1.NeuralNet Adaptative on-line single pattern training
adapt.C2.NeuralNet Adaptative on-line single pattern training
adapt.C3.NeuralNet Adaptative on-line single pattern training
adapt.NeuralNet Adaptative on-line single pattern training
adapt.R.NeuralNet Adaptative on-line single pattern training
backpropagate.adapt.C.NeuralNet Backpropagates the single pattern error modifying accordingly the Neural Network's weights and biases.
backpropagate.adapt.R.NeuralNet Backpropagates the single pattern error modifying accordingly the Neural Network's weights and biases.
backpropagate.adapt.R.neuron Backpropagates the single pattern error modifying accordingly the neuron's weights and bias.
deltaE.LMLS Neural network training error criteria.
deltaE.MSE Neural network training error criteria.
deltaE.TAO Neural network training error criteria.
dphifun TAO robust error criterium auxiliar functions.
error.LMLS Neural network training error criteria.
error.MSE Neural network training error criteria.
error.TAO Neural network training error criteria.
forward.adapt.C.NeuralNet Perform the forward pass in the adaptative training.
forward.adapt.R.NeuralNet Perform the forward pass in the adaptative training.
forward.adapt.R.neuron Perform the neuron forward pass in the adaptative training.
forwardpass.C.NeuralNet Simulate a Neural Network response.
forwardpass.R.NeuralNet Simulate a Neural Network response.
forwardpass.R.neuron Simulate a neuron response.
hfun TAO robust error criterium auxiliar functions.
init.neuron Neuron constructor.
newff Feedforward Neural Network
phifun TAO robust error criterium auxiliar functions.
random.init.NeuralNet Initialize the network with random weigths and biases.
random.init.neuron Initialize the neuron with random weigths and bias.
restrict Restrict the patterns to the [-1,1] interval.
select.activation.function Provides R code of the selected activation function.
set.learning.rate.and.momentum Set Learning rate and momentum.
sim.C.NeuralNet Performs the simulation of a neural network providing the output values.
sim.NeuralNet Performs the simulation of a neural network providing the output values.
sim.R.NeuralNet Performs the simulation of a neural network providing the output values.
train Neural network training function.
train.compare Trains the same neural network according to different error criteria.
training.report Neural network training report generator function.