Presentation 2014-11-18
Coping with Class Balance Change in Classification : Class-Prior Estimation with Energy Distance
Hideko KAWAKUBO, PLESSIS Christoffel DU, Masashi SUGIYAMA,
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Abstract(in English) Due to sample selection bias or non-stationarity of the environment, the class balance often changes between training and test datasets. Naive classifier training under such a situation yields a biased solution. This bias can be corrected by weighted training according to the test class balance, but this test class balance is often unknown in practice. In this paper, we consider a semi-supervised learning setup where labeled training samples and unlabeled test samples are available, and address the problem of class balance estimation. It was shown that the test class balance can be estimated by fitting a mixture of class-wise training input distributions to the test input distribution, and class balance estimators were developed under, e.g., the Kullback-Leibler divergence and the L_2 distance. In this paper, we propose a simple class balance estimator based on the energy distance and demonstrate its usefulness through experiments.
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Keyword(in English) Class balance change / class-prior estimation / energy distance
Paper # IBISML2014-71
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Committee IBISML
Conference Date 2014/11/10(1days)
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Registration To Information-Based Induction Sciences and Machine Learning (IBISML)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Coping with Class Balance Change in Classification : Class-Prior Estimation with Energy Distance
Sub Title (in English)
Keyword(1) Class balance change
Keyword(2) class-prior estimation
Keyword(3) energy distance
1st Author's Name Hideko KAWAKUBO
1st Author's Affiliation Tokyo Institute of Technology()
2nd Author's Name PLESSIS Christoffel DU
2nd Author's Affiliation The University of Tokyo
3rd Author's Name Masashi SUGIYAMA
3rd Author's Affiliation The University of Tokyo
Date 2014-11-18
Paper # IBISML2014-71
Volume (vol) vol.114
Number (no) 306
Page pp.pp.-
#Pages 8
Date of Issue