Algorithm 1.

Dimension reduction by Information Gain and ReliefF

Input: train instances of D (merged datasets), classifierType(classification or regression)

Output: Dataset with ranked best features S

for each feature array A do

if classifierType = classification

then meritScorea = Compute information gain

value of A with respect to classes Y

else meritScorea = Compute ReliefF value of a

with respect to classes Y

end if

if meritScorea≠0

then add | meritScorea |to meritScores

end if

end for

SortedFeatures = Sort meritScores from largest to smallest values

if |SortedFeatures| ≤ 1000

then S = SortedFeatures

else S = SortedFeatures{A1, A2, …, A1000}

end if

return S