A maximal coverage entropy based reduct for classification

The paper proposes a new scoring metric to rank a reduct. Our technique investigates each reduct against the decision table data for ranking by coupling entropy score and coverage score. We compared our work result to a result from a feature selection technique in Weka. The result showed the model learned from our selected features yielded higher accuracy.