Classification using Multilayer Perceptron
This function builds a classification model using Multilayer Perceptron.
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,
...
)train |
The training set (description), as a |
labels |
Class labels of the training set ( |
hidden |
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. |
The classification model.
## Not run: require (datasets) data (iris) MLP (iris [, -5], iris [, 5], hidden = 4, decay = .1) ## End(Not run)
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