LCC {FSinR}

Linear Consistency-Constrained algorithm

Description

Generates a hybrid search function based on Linear Consistency-Constrained algorithm described in (Shin and Xu 2009). 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

Shin K, Xu XM (2009). “Consistency-Based Feature Selection.” In Knowledge-Based and Intelligent Information and Engineering Systems, 342–350. ISBN 978-3-642-04595-0.

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)