mutualInformation {FSinR}

The mutual information measure

Description

Generates an evaluation function that calculates the mutual information value, using the information theory (Qian and Shu 2015) (set measure). This function is called internally within the filterEvaluator function.

Usage

mutualInformation()

Value

Returns a function that is used to generate an evaluation set measure using the mutual information value for the selected features.

Author(s)

Adan M. Rodriguez

References

Qian W, Shu W (2015). “Mutual information criterion for feature selection from incomplete data.” Neurocomputing, 168, 210–220. doi: 10.1016/j.neucom.2015.05.105.

Examples

## Not run:  

## The direct application of this function is an advanced use that consists of using this 
# function directly to evaluate a set of features
## Classification problem

# A discrete dataset is used (in this case we use only several discrete columns)
adult <- adult[,c(4,9,10,15)]

# Generate the evaluation function with Cramer
mi_evaluator <- mutualInformation()
# Evaluate the features (parameters: dataset, target variable and features)
mi_evaluator(adult,'income',c('race','sex','education'))

## End(Not run)