FSinR (version 1.0.8)

sfbs: Sequential Floating Backward Selection

Description

The sfbs method Pudil1994FSinR starts with all the features and removes a single feature at each step with a view to improving the evaluation of the set. In addition, it checks whether adding any of the removed features, improve the value of the set.

Usage

sfbs(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 {
## sfbs method for iris dataset (filter method)
sfbs(iris, 'Species', determinationCoefficient)
# }