searchAlgorithm: Search algorithm generator

In FSinR: Feature Selection

Description

Generates a search function. This function in combination with the evaluator guides the feature selection process. Specifically, the result of calling this function is another function that is passed on as a parameter to the featureSelection function. However, you can run this function directly to perform a search process in the features space.

Usage

searchAlgorithm(searcher, params = list())

Arguments

searcher

Name of the search algorithm. The available search algorithms are: antColony Ant colony optimization (ACO). See antColony breadthFirst Breadth first search. See breadthFirst deepFirst Deep first search. See deepFirst geneticAlgorithm Genetic algorithm (GA). See geneticAlgorithm hillClimbing Hill-Climbing (HC). See hillClimbing LasVegas Las Vegas (LV). See LasVegas sequentialBackwardSelection Sequential backward selection (sbs). See sequentialBackwardSelection sequentialFloatingForwardSelection Sequential floating forward selection (sffs). See sequentialFloatingForwardSelection sequentialFloatingBackwardSelection Sequential floating backward selection (sfbs). See sequentialFloatingBackwardSelection sequentialForwardSelection Sequential forward selection (sfs). See sequentialForwardSelection simulatedAnnealing Simulated annealing (SA). See simulatedAnnealing tabu Tabu search (TS). See tabu whaleOptimization Whale optimization algorithm (WOA). See whaleOptimization

params

List with the parameters of each search method. For more details see each method. Default: empty list.

Value

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

Author(s)

Francisco Aragón Royón

References

\insertAllCited

Examples

## Not run:  

## Examples of a search algorithm generation

search_method_1 <- searchAlgorithm('antColony')
search_method_2 <- searchAlgorithm('sequentialBackwardSelection')
search_method_3 <- searchAlgorithm('tabu')


## Examples of a search algorithm generation (with parameters)

search_method_1 <- searchAlgorithm('antColony', list(population=25, iter=50, verbose=TRUE))
search_method_2 <- searchAlgorithm('sequentialBackwardSelection', list(stop=TRUE))
search_method_3 <- searchAlgorithm('tabu', list(intensification=1, iterIntensification=25))


## The direct application of this function is an advanced use that consists of using this 
# function directly to perform a search process on a feature space
## Classification problem

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

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

## End(Not run)

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