sequentialForwardSelection: Sequential Forward Selection

In FSinR: Feature Selection

Description

Generates a search function based on sequential forward selection. This function is called internally within the searchAlgorithm function. The SFS method \insertCiteWhitney1971FSinR 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.

Usage

sequentialForwardSelection(stopCriterion = -1, stop = FALSE)

Arguments

stopCriterion	Define a maximum number of iterations. Disabled if the value is -1 (default: -1 )
stop	If true, the function stops if next iteration does not improve current results (default: FALSE)

Value

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

Author(s)

Adan M. Rodriguez

Alfonso Jiménez-Vílchez

Francisco Aragón Royón

References

\insertAllCited

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 with sfs
filter_evaluator <- filterEvaluator('determinationCoefficient')

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

## End(Not run)

FSinR documentation built on Nov. 23, 2020, 5:10 p.m.