LCC: Linear Consistency-Constrained algorithm

In FSinR: Feature Selection

Description

Generates a hybrid search function based on Linear Consistency-Constrained algorithm described in \insertCiteShinXu2009FSinR. The algorithm combines two evaluation measures, the first evaluates each feature individually, and the second measure evaluate feature sets.

Usage

LCC(threshold = 0.9)

Arguments

threshold

Threshold

Value

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

Author(s)

Alfonso Jiménez-Vílchez

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 hybrid search process in 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 with LCC
LCC_hybrid_search <- LCC()
# Run the search process directly (params: dataset, target variable, evaluator1 & evaluator2)
LCC_hybrid_search(iris, 'Species', filter_evaluator_1, filter_evaluator_2)

## End(Not run)

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