Using Ensemble Feature Selection Approach in Selecting Subset with Relevant Features

Abstract

AbstractThis study discusses the problem of feature selection as one of the most fundamental problems in the field of the machine learning. Two novel approaches for feature selection in order to select a subset with relevant features are proposed. These approaches can be considered as a direct extension of the ensemble feature selection approach. The first one deals with identifying relevant features by using a single feature selection method. While, the second one uses different feature selection methods in order to identify more correctly the relevant features. An illustration shows the effectiveness of the proposed methods on artificial databases where we have a priori the informations about the relevant features.KeywordsFeature SelectionRelevant FeatureFeature SubsetFeature Selection MethodNeural Information Processing SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.