sequentialFloatingBackwardSelection {FSinR}

Sequential Floating Backward Selection

Description

Generates a search function based on sequential floating backward selection. This function is called internally within the searchAlgorithm function. The sfbs method (Pudil et al. 1994) 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

sequentialFloatingBackwardSelection()

Value

Returns a search function that is used to guide the feature selection process.

Author(s)

Adan M. Rodriguez

Francisco Aragón Royón

References

Pudil P, Novovičová J, Kittler J (1994). “Floating search methods in feature selection.” Pattern recognition letters, 15, 1119–1125.

Examples

## Not run:  

## The direct application of this function is an advanced use that consists of using this 
# function directly and performing a search process in a feature space
## Classification problem

# Generates the filter evaluation function
filter_evaluator <- filterEvaluator('determinationCoefficient')

# Generates the search function with sfbs
sfbs_search <- sequentialFloatingBackwardSelection()
# Performs the search process directly (parameters: dataset, target variable and evaluator)
sfbs_search(iris, 'Species', filter_evaluator)

## End(Not run)