filter methods, feature selection or weighting are done as a preprocess and are considered as independent to the late learning procedure; b) wrapper methods, selection and weighting are performed by using the same algorithm as the late learning process, so the quality is influenced by the accuracy and performance of the algorithm . Most of the time, filter methods are faster, more general, and cheaper in terms of computation cost and time. Additionally, they do not suffer from biased estimation of features subgroup and not have the shortcoming of guessing a cutting threshold .