TY - JOUR
TI - On the Consistency of Multithreshold Entropy Linear Classifier
AU - Czarnecki, Wojciech Marian
TI - On the Consistency of Multithreshold Entropy Linear Classifier
AB - 
	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.
VL - 2015
IS - Volume 24
PY - 2016
SN - 1732-3916
C1 - 2083-8476
SP - 123
EP - 132
DO - 10.4467/20838476SI.15.012.3034
UR - https://ejournals.eu/en/journal/schedae-informaticae/article/on-the-consistency-of-multithreshold-entropy-linear-classifier
KW - multithreshold classifier
KW - entropy
KW - consistency
KW - classification theory