MLP {fdm2id} | R Documentation |
Classification using Multilayer Perceptron
Description
This function builds a classification model using Multilayer Perceptron.
Usage
MLP(
train,
labels,
hidden = ifelse(is.vector(train), 2:(1 + nlevels(labels)), 2:(ncol(train) +
nlevels(labels))),
decay = 10^(-3:-1),
methodparameters = NULL,
tune = FALSE,
...
)
Arguments
train |
The training set (description), as a |
labels |
Class labels of the training set ( |
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). |
methodparameters |
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.
See Also
Examples
## Not run:
require (datasets)
data (iris)
MLP (iris [, -5], iris [, 5], hidden = 4, decay = .1)
## End(Not run)
[Package fdm2id version 0.9.9 Index]