Description Usage Value Author(s) References Examples
View source: R/sequentialSelection.R
Generates a search function based on sequential floating backward selection. This function is called internally within the searchAlgorithm
function. The sfbs method \insertCitePudil1994FSinR 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.
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Returns a search function that is used to guide the feature selection process.
Adan M. Rodriguez
Francisco Aragón Royón
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## 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)
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