Classification using CART
This function builds a classification model using CART.
CART( train, labels, minsplit = 1, maxdepth = log2(length(labels)), cp = NULL, tune = FALSE, ... )
train |
The training set (description), as a |
labels |
Class labels of the training set ( |
minsplit |
The minimum leaf size during the learning. |
maxdepth |
Set the maximum depth of any node of the final tree, with the root node counted as depth 0. |
cp |
The complexity parameter of the tree. Cross-validation is used to determine optimal cp if NULL. |
tune |
If true, the function returns paramters instead of a classification model. |
... |
Other parameters. |
The classification model.
require (datasets) data (iris) CART (iris [, -5], iris [, 5])
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