FSinR (version 1.0.8)

sffs: Sequential Floating Forward Selection

Description

The sffs method Pudil1994FSinR starts with an empty set of features and add a single feature at each step with a view to improving the evaluation of the set. In addition, it checks whether removing any of the included features, improve the value of the set.

Usage

sffs(data, class, featureSetEval)

Arguments

data

• A data frame with the features and the class of the examples

class

• The name of the dependent variable

featureSetEval

• The measure for evaluate features

Value

A list is returned containing:

bestFeatures

A vector with all features. Selected features are marked with 1, unselected features are marked with 0

bestFitness

Evaluation measure obtained with the feature selection

References

Examples

# NOT RUN {
## sffs method for mtcars dataset (filter method)
sffs(mtcars, 'mpg', mutualInformation)
# }