Classification using Random Forest
This function builds a classification model using Random Forest
RANDOMFOREST(
train,
labels,
ntree = 500,
nvar = if (!is.null(labels) && !is.factor(labels)) max(floor(ncol(train)/3), 1) else
floor(sqrt(ncol(train))),
tune = FALSE,
...
)train |
The training set (description), as a |
labels |
Class labels of the training set ( |
ntree |
The number of trees in the forest. |
nvar |
Number of variables randomly sampled as candidates at each split. |
tune |
If true, the function returns paramters instead of a classification model. |
... |
Other parameters. |
The classification model.
## Not run: require (datasets) data (iris) RANDOMFOREST (iris [, -5], iris [, 5]) ## End(Not run)
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