hybridSearchAlgorithm {FSinR}

Hybrid search algorithm generator

Description

Generates a hybrid 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

hybridSearchAlgorithm(hybridSearcher, params = list())

Arguments

hybridSearcher

Name of the hybrid search algorithm. The available hybrid search algorithms are:

LCC

Linear Consistency-Constrained algorithm (LCC). See LCC

params

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

Value

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

Author(s)

Francisco Aragón Royón

References

There are no references for Rd macro ⁠\insertAllCites⁠ on this help page.

Examples

## Not run:  

## Examples of a hybrid search algorithm generation

hybrid_search_method <- hybridSearchAlgorithm('LCC')


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

hybrid_search_method <- hybridSearchAlgorithm('LCC', list(threshold = 0.8))



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

# Generates the first filter evaluation function (individual or set measure)
filter_evaluator_1 <- filterEvaluator('determinationCoefficient')
# Generates the second filter evaluation function (mandatory set measure)
filter_evaluator_2 <- filterEvaluator('ReliefFeatureSetMeasure')

# Generates the hybrid search function
hybrid_search_method <- hybridSearchAlgorithm('LCC')
# Run the search process directly (params: dataset, target variable, evaluator1 & evaluator2)
hybrid_search_method(iris, 'Species', filter_evaluator_1, filter_evaluator_2)

## End(Not run)