SVM with a neutral class

doi:10.1007/s10044-017-0654-3

SVM with a neutral class

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SVM with a neutral class

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Bibliographic description

punktacja MEiN [2019]: 70

title:	SVM with a neutral class
author:	Śmieja Marek , Tabor Jacek , Spurek Przemysław
journal title:	Pattern Analysis and Applications
volume:	22
issue:	2
date of publication :	2019
pages:	573-582
ISSN:	1433-7541
eISSN:	1433-755X
DOI:	10.1007/s10044-017-0654-3
language:	English
journal language:	English
abstract in English:	In many real binary classification problems, in addition to the presence of positive and negative classes, we are also given the examples of third neutral class, i.e., the examples with uncertain or intermediate state between positive and negative. Although it is a common practice to ignore the neutral class in a learning process, its appropriate use can lead to the improvement in classification accuracy. In this paper, to include neutral examples in a training stage, we adapt two variants of Tri-Class SVM (proposed by Angulo et al. in Neural Process Lett 23(1):89–101, 2006), the method designed to solve three-class problems with a use of single learning model. In analogy to classical SVM, we look for such a hyperplane, which maximizes the margin between positive and negative instances and which is localized as close to the neutral class as possible. In addition to original Angulo’s paper, we give a new interpretation of the model and show that it can be easily implemented in the primal. Our experiments demonstrate that considered methods obtain better results in binary classification problems than classical SVM and semi-supervised SVM.
keywords in English:	classification, SVM, semi-supervised learning, cheminformatics
affiliation:	Wydział Matematyki i Informatyki : Instytut Informatyki i Matematyki Komputerowej
type:	journal article
subtype:	academic paper