MLPREG {fdm2id} | R Documentation |
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 |
y |
Response |
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 |
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
Examples
## Not run:
require (datasets)
data (trees)
MLPREG (trees [, -3], trees [, 3])
## End(Not run)
[Package fdm2id version 0.9.9 Index]