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Training Classifiers under Covariate Shift by Constructing the Maximum Consistent Distribution Subset
Joint Authors
Yang, Jing
Yu, Xu
Yu, Miao
Xu, Li-xun
Xie, Zhi-qiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-09
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The assumption that the training and testing samples are drawn from the same distribution is violated under covariate shift setting, and most algorithms for the covariate shift setting try to first estimate distributions and then reweight samples based on the distributions estimated.
Due to the difficulty of estimating a correct distribution, previous methods can not get good classification performance.
In this paper, we firstly present two types of covariate shift problems.
Rather than estimating the distributions, we then desire an effective method to select a maximum subset following the target testing distribution based on feature space split from the auxiliary set or the target training set.
Finally, we prove that our subset selection method can consistently deal with both scenarios of covariate shift.
Experimental results demonstrate that training a classifier with the selected maximum subset exhibits good generalization ability and running efficiency over those of traditional methods under covariate shift setting.
American Psychological Association (APA)
Yu, Xu& Yu, Miao& Xu, Li-xun& Yang, Jing& Xie, Zhi-qiang. 2015. Training Classifiers under Covariate Shift by Constructing the Maximum Consistent Distribution Subset. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073464
Modern Language Association (MLA)
Yu, Xu…[et al.]. Training Classifiers under Covariate Shift by Constructing the Maximum Consistent Distribution Subset. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1073464
American Medical Association (AMA)
Yu, Xu& Yu, Miao& Xu, Li-xun& Yang, Jing& Xie, Zhi-qiang. Training Classifiers under Covariate Shift by Constructing the Maximum Consistent Distribution Subset. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073464
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073464