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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.