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Density Ratio Estimation in Machine Learning

Language EnglishEnglish
Book Hardback
Book Density Ratio Estimation in Machine Learning Masashi Sugiyama
Libristo code: 02069414
Publishers Cambridge University Press, February 2012
Machine learning is an interdisciplinary field of science and engineering that studies mathematical... Full description
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Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric convergence analysis and numerical stability analysis to complete the first and definitive treatment of the entire framework of density ratio estimation in machine learning.

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About the book

Full name Density Ratio Estimation in Machine Learning
Language English
Binding Book - Hardback
Date of issue 2012
Number of pages 342
EAN 9780521190176
ISBN 0521190177
Libristo code 02069414
Weight 598
Dimensions 157 x 240 x 23
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