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 |
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. |
The classification model, as an object of class model-class
.
## Not run: require (datasets) data (trees) MLPREG (trees [, -3], trees [, 3]) ## End(Not run)
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