Algorithm A1. Minimum-Redundancy-Maximum-Relevance for regression.
	INPUT:	candidateFeatures // set of features to be ranked.
		Y        // target variable.
	OUTPUT:	rankedFfeatures  // features ranked
1:	for feature i in candidateFeatures do
2:		relevance = MI (i, Y);
3:		redundancy = 0;
4:		for feature j in candidateFeatures do
5:			redundancy = redundancy + MI (i,j);
6:		end for
7:		mrmrValues[ i ] = relevance − redundancy;
8:	end for
9:	rankedFeatures = sort(mrmrValues);