An Evolutionary Approach to Feature Set Selection
نویسنده
چکیده
This paper investigates an ensemble feature selection algorithm that is based on genetic algorithms. The task of ensemble feature selection is harder than traditional feature selection in that one not only needs to find features germane to the learning task and learning algorithm, but one also needs to find a set of feature subsets that will promote disagreement among the ensemble’s classifiers. Our algorithm shows improved performance over the popular and powerful ensemble approaches of AdaBoost and Bagging.
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