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Geometric Mean based Boosting Algorithm

Authors:
Myoung Jong Kim

Keywords: data imbalance; GM-Boost; bankruptcy prediction

Abstract:
Abstract-Data imbalance problem has received a lot of attention in machine learning community because it is one of the causes that degrade the performance of classifiers or predictors. In this paper, we propose geometric mean based boosting algorithm (GM-Boost) to resolve the data imbalance problem. GM-Boost enables learning with consideration of both majority and minority classes because it uses the geometric mean of both classes in error rate and accuracy calculation. We have applied GM-Boost to bankruptcy prediction task. The results indicate that GM-Boost has the advantages of high prediction power and robust learning capability in imbalanced data as well as balanced data distribution.

Pages: 15 to 20

Copyright: Copyright (c) IARIA, 2013

Publication date: January 27, 2013

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-247-9

Location: Seville, Spain

Dates: from January 27, 2013 to February 1, 2013