Interactive evolutionary approaches to multi-objective feature selection

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Bilimleri Enstitüsü, Fen Bilimleri Enstitüsü, Türkiye

Tezin Onay Tarihi: 2016

Tezin Dili: İngilizce

Öğrenci: Müberra Özmen

Asıl Danışman (Eş Danışmanlı Tezler İçin): Mustafa Murat Köksalan

Eş Danışman: Gülşah Karakaya

Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu

Özet:

In feature selection problems, the aim is to select a subset of features to characterize an output of interest. In characterizing an output, we may want to consider multiple objectives such as maximizing classification performance, minimizing number of selected features or cost, etc. We develop a preference-based approach for multi-objective feature selection problems. Finding all Pareto optimal subsets may turn out to be a computationally demanding problem and we still would need to select a solution eventually. Therefore, we develop interactive evolutionary approaches that aim to converge to a subset that is highly preferred by the decision maker. We test our approach on several instances simulating decision-maker preferences by underlying preference functions and demonstrate that it works well.