Feature selection is an effective technique to reduce the dimensionality of a data set and to select relevant features for the domain problem. Recently, stability of feature selection methods has gained increasing attention. In fact, it has become a crucial factor in determining the goodness of a feature selection algorithm besides the learning performance. In this work, we conduct an extensive experimental study using verity of data sets and different well-known feature selection algorithms in order to study the behavior of these algorithms in terms of the stability.
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Alelyani et al. (2011) studied this question.
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