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. |