RSNNS (version 0.3-1)

rbfDDA: Create and train a rbf network with the DDA algorithm.

Description

Create and train a rbf network with the DDA algorithm.

Usage

rbfDDA(x, ...)
## S3 method for class 'default':
rbfDDA(x, y, maxit=1, initFunc="Randomize_Weights", initFuncParams=c(-0.3,
    0.3), learnFunc="RBF-DDA", learnFuncParams=c(0.4, 0.2, 5),
    updateFunc="Topological_Order", updateFuncParams=c(0),
    shufflePatterns=TRUE, linOut=FALSE, ...)

Arguments

x

a matrix with training inputs for the network

y

the corresponding targets values

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

shufflePatterns

should the patterns be shuffled?

linOut

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

...

additional function parameters (currently not used)

Value

• rbfDDA.default: an rsnns object.

Details

rbfDDA: As the output is winner-takes-all, this type of net can only be used for classification.

Examples

demo(iris)
demo(rbfDDA_spiralsSnnsR)