On the Consistency of Multithreshold Entropy Linear Classifier

• Autorzy: Czarnecki W. M.

Identyfikatory

DOI

10.4467/20838476SI.15.012.3034

• Języki publikacji: EN

Abstrakty

EN

Multithreshold Entropy Linear Classifier (MELC) is a recent classifier idea which employs information theoretic concept in order to create a multithreshold maximum margin model. In this paper we analyze its consistency over multithreshold linear models and show that its objective function upper bounds the amount of misclassified points in a similar manner like hinge loss does in support vector machines. For further confirmation we also conduct some numerical experiments on five datasets.

Słowa kluczowe

EN

multithreshold classifier; entropy; consistency; classification theory

• Wydawca: Wydawnictwo Uniwersytetu Jagiellońskiego
• Czasopismo: Schedae Informaticae
• Rocznik: 2015
• Tom: Vol. 24
• Strony: 123--132
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Czarnecki W. M.

• Faculty of Mathematics and Computer Science Jagiellonian University ul. Łojasiewicza 6, 30-348 Kraków

Bibliografia

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