Feature selection for classification
Select a subset of features for a classification task.
selectfeatures( train, labels, algorithm = c("ranking", "forward", "backward", "exhaustive"), unieval = if (algorithm[1] == "ranking") c("fisher", "fstat", "relief", "inertiaratio") else NULL, uninb = NULL, unithreshold = NULL, multieval = if (algorithm[1] == "ranking") NULL else c("mrmr", "cfs", "fstat", "inertiaratio", "wrapper"), wrapmethod = NULL, keep = FALSE, ... )
train |
The training set (description), as a |
labels |
Class labels of the training set ( |
algorithm |
The feature selection algorithm. |
unieval |
The (univariate) evaluation criterion. |
uninb |
The number of selected feature (univariate evaluation). |
unithreshold |
The threshold for selecting feature (univariate evaluation). |
multieval |
The (multivariate) evaluation criterion. |
wrapmethod |
The classification method used for the wrapper evaluation. |
keep |
If true, the dataset is kept in the returned result. |
... |
Other parameters. |
## Not run: require (datasets) data (iris) selectfeatures (iris [, -5], iris [, 5], algorithm = "forward", multieval = "fstat") selectfeatures (iris [, -5], iris [, 5], algorithm = "ranking", uninb = 2) selectfeatures (iris [, -5], iris [, 5], algorithm = "ranking", multieval = "wrapper", wrapmethod = LDA) ## End(Not run)
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