miller.4314

I need help with a problem in my CS420 Data Mining course. The question asks to use the Relief Algorithm for feature selection. The algorithm is as follows: W(A­i)new = W(Ai)old – (diff(X[Ai], H[Ai])2 + diff(X[Ai], M[Ai])2)/m where W(Ai) is the quality score for all feature Ai, X is a randomly selected sample, H is nearest Hit, M is nearest Miss, and m is the number of randomly selected training samples. Any help with this problem would be greatly appreciated. Thanks!