MLPREG: Multi-Layer Perceptron Regression

In fdm2id: Data Mining and R Programming for Beginners

Multi-Layer Perceptron Regression

Description

This function builds a regression model using MLP.

Usage

MLPREG(
  x,
  y,
  size = 2:(ifelse(is.vector(x), 2, ncol(x))),
  decay = 10^(-3:-1),
  params = NULL,
  tune = FALSE,
  ...
)

Arguments

x	Predictor matrix.
y	Response vector.
size	The size of the hidden layer (if a vector, cross-over validation is used to chose the best size).
decay	The decay (between 0 and 1) of the backpropagation algorithm (if a vector, cross-over validation is used to chose the best size).
params	Object containing the parameters. If given, it replaces size and decay.
tune	If true, the function returns paramters instead of a classification model.
...	Other parameters.

Value

The classification model, as an object of class model-class.

See Also

nnet

Examples

## Not run: 
require (datasets)
data (trees)
MLPREG (trees [, -3], trees [, 3])

## End(Not run)

fdm2id documentation built on July 9, 2023, 6:05 p.m.