Missing Data Problems in Machine Learning

Name: Missing Data Problems in Machine Learning
Brand: VDM Verlag
SKU: 9783639212280
Price: 378.61 RON
Availability: InStock

Outline and Contributions

Autor: Robin Parker

Limbă:

Legare: Carte broșată

Editura: VDM Verlag

Disponibilitate: În depozitul extern

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

Informații despre carte

Autor

Robin Parker

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

168

EAN

9783639212280

ISBN

3639212282

Enbook ID

06829144

Editura

VDM Verlag

Greutate

254

Dimensiuni

152 x 229 x 10

Descriere completă

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

Informații despre carte

Descriere completă

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