Visualization and Analysis Tools for Neural Networks

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Documentation for package ‘NeuralNetTools’ version 1.3.1

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garson Variable importance using Garson's algorithm
garson.mlp Variable importance using Garson's algorithm
garson.nn Variable importance using Garson's algorithm
garson.nnet Variable importance using Garson's algorithm
garson.numeric Variable importance using Garson's algorithm
garson.train Variable importance using Garson's algorithm
lekprofile Sensitivity analysis based on Lek's profile method
lekprofile.default Sensitivity analysis based on Lek's profile method
lekprofile.mlp Sensitivity analysis based on Lek's profile method
lekprofile.nnet Sensitivity analysis based on Lek's profile method
lekprofile.train Sensitivity analysis based on Lek's profile method
neuraldat Simulated dataset for function examples
neuralskips Get weights for the skip layer in a neural network
neuralskips.nnet Get weights for the skip layer in a neural network
neuralweights Get weights for a neural network
neuralweights.mlp Get weights for a neural network
neuralweights.nn Get weights for a neural network
neuralweights.nnet Get weights for a neural network
neuralweights.numeric Get weights for a neural network
olden Variable importance using connection weights
olden.mlp Variable importance using connection weights
olden.nn Variable importance using connection weights
olden.nnet Variable importance using connection weights
olden.numeric Variable importance using connection weights
olden.train Variable importance using connection weights
plotnet Plot a neural network model
plotnet.mlp Plot a neural network model
plotnet.nn Plot a neural network model
plotnet.nnet Plot a neural network model
plotnet.numeric Plot a neural network model
plotnet.train Plot a neural network model
pred_sens Predicted values for Lek profile method