fdm2id: MLPREG – R documentation

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MLPREG

Multi-Layer Perceptron Regression

This function builds a regression model using MLP.

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

`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.

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

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

## End(Not run)

Data Mining and R Programming for Beginners

v0.9.5

GPL-3

Authors

Alexandre Blansché [aut, cre]

Initial release