PL EN


Preferences help
enabled [disable] Abstract
Number of results
2015 | 24 |
Article title

On the Consistency of Multithreshold Entropy Linear Classifier

Content
Title variants
Languages of publication
PL
Abstracts
PL
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.
Publisher
Year
Volume
24
Physical description
Dates
published
2015
online
06 - 07 - 2016
Contributors
References
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.ojs-issn-2083-8476-year-2015-volume-24-article-6340
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.