Missing Data Problems in Machine Learning

Name: Missing Data Problems in Machine Learning
Brand: VDM Verlag
SKU: 9783639212280
Price: 1583 CZK
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Outline and Contributions

Autor: Robin Parker

Jazyk:

Vazba: Brožovaná

Vydavatel: VDM Verlag

Dostupnost: Skladem u dodavatele

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1 583 Kč

Learning, inference, and prediction in the presence of missing data are pervasive problems in machin...

Informace o knize

Autor

Robin Parker

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2010

Stránek

168

EAN

9783639212280

ISBN

3639212282

Enbook ID

06829144

Vydavatel

VDM Verlag

Hmotnost

254

Rozměry

152 x 229 x 10

Kompletní popis

Learning, inference, and prediction in the presence of missing data are pervasive problems in machine learning and statistical data analysis. This thesis focuses on the problems of collaborative prediction with non-random missing data and classification with missing features. We begin by presenting and elaborating on the theory of missing data due to Little and Rubin. We place a particular emphasis on the missing at random assumption in the multivariate setting with arbitrary patterns of missing data. We derive inference and prediction methods in the presence of random missing data for a variety of probabilistic models including finite mixture models, Dirichlet process mixture models, and factor analysis.

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Missing Data Problems in Machine Learning

Outline and Contributions

Informace o knize

Kompletní popis

Mohlo by vás zajímat

Zákaznicí kteří koupili tuto knihu koupili také