RSNNS (version 0.3-1)

mlp: Create and train a multi-layer perceptron (mlp).

Description

Create and train a multi-layer perceptron (mlp).

Usage

mlp(x, ...)
## S3 method for class 'default':
mlp(x, y, size=c(5), maxit=100, initFunc="Randomize_Weights",
    initFuncParams=c(-0.3, 0.3), learnFunc="Quickprop",
    learnFuncParams=c(0.2), updateFunc="Topological_Order",
    updateFuncParams=c(0), hiddenActFunc="Act_Logistic",
    shufflePatterns=TRUE, linOut=FALSE, inputsTest, targetsTest, ...)

Arguments

x

a matrix with training inputs for the network

y

the corresponding targets values

size

number of units in the hidden layer(s)

maxit

maximum of iterations to learn

initFunc

the initialization function to use

initFuncParams

the parameters for the initialization function

learnFunc

the learning function to use

learnFuncParams

the parameters for the learning function

updateFunc

the update function to use

updateFuncParams

the parameters for the update function

hiddenActFunc

the activation function of all hidden units

shufflePatterns

should the patterns be shuffled?

linOut

sets the activation function of the output units to linear or logistic

inputsTest

a matrix with inputs to test the network

targetsTest

the corresponding targets for the test input

...

additional function parameters (currently not used)

Value

• mlp.default: an rsnns object.

Examples

demo(iris)
demo(laser)
demo(encoderSnnsCLib)