Machine learning in non-stationary environments : introduction to covariate shift adaptation /

This volume focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) changes but the conditional distributions of outputs (answers) is unchanged, and presents machine learning theory algorithms, and applications to overcome this variet...

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Bibliographic Details
Main Author: Sugiyama, Masashi, 1974-
Other Authors: Kawanabe, Motoaki
Format: eBook
Language:English
Published: Cambridge, Mass. : MIT Press, ©2012.
Series:Adaptive computation and machine learning
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:This volume focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) changes but the conditional distributions of outputs (answers) is unchanged, and presents machine learning theory algorithms, and applications to overcome this variety of non-stationarity.
Physical Description:1 online resource (xiv, 261 pages) : illustrations.
ISBN:9780262301220
0262301229
1280499222
9781280499227
DOI:10.7551/mitpress/9780262017091.001.0001