Volume 6, Issue 1 (Journal of Control, V.6, N.1 Spring 2012)                   JoC 2012, 6(1): 9-19 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Bagheri M A, Montazer G. An Efficient Multiclass Classification Method Based on Classifier Selection Technique. JoC. 2012; 6 (1) :9-19
URL: http://joc.kntu.ac.ir/article-1-64-en.html
Abstract:   (6561 Views)
Individual classification models have recently been challenged by ensemble of classifiers, also known as multiple classifier system, which often shows better classification accuracy. In terms of merging the outputs of an ensemble of classifiers, classifier selection has not attracted as much attention as classifier fusion in the past, mainly because of its higher computational burden. In this paper, we propose a novel technique for improving classifier selection. In our method, the simple divide-and-conquer strategy is adapted in that a complex classification problem is divided into simpler binary sub-classification problems. We conduct extensive experiments on a series of multi-class datasets from the UCI (University of California, Irvine) repository and on odor database. The experimental results demonstrate the advanced performance of the proposed method.
Full-Text [PDF 1178 kb]   (1232 Downloads)    
Type of Article: Research paper | Subject: Special
Received: 2014/06/14 | Accepted: 2014/06/14 | Published: 2014/06/14

Add your comments about this article : Your username or Email:

Send email to the article author

© 2020 All Rights Reserved | Journal of Control

Designed & Developed by : Yektaweb