Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/92068
Type: Artigo de evento
Title: Multi-class From Binary: Divide To Conquer
Author: Rocha A.
Goldenstein S.
Abstract: Several researchers have proposed effective approaches for binary classification in the last years. We can easily extend some of those techniques to multi-class. Notwithstanding, some other powerful classifiers (e.g., S VMs) are hard to extend to multi-class. In such cases, the usual approach is to reduce the multi-class problem complexity into simpler binary classification problems (divide-and-conquer). In this paper, we address the multi-class problem by introducing the concept of affine relations among binary classifiers (dichotomies), and present a principled way to find groups of high correlated base learners. Finally, we devise a strategy to reduce the number of required dichotomies in the overall multi-class process.
Editor: 
Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-70349653822&partnerID=40&md5=470c24c1a71caec216d87cf817a98776
Date Issue: 2009
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-70349653822.pdf135.02 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.