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Mixture Model-Based Classification
Mixture Model-Based Classification

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This work addresses classification using mixture models broadly. Unlike traditional treatments of the subject that heavily focus on unsupervised approaches, this book gives attention to unsupervised, semi-supervised, and supervised classification paradigms. Case studies illustrate both non-Gaussian and Gaussian approaches to model selection.

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  • Author Paul David McNicholas
  • ISBN13 9781482225662
  • ISBN10 1482225662
  • Pages 210
  • Published 2015
  • Fecha de publicación 26/12/2015
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Mixture Model-Based Classification

Mixture Model-Based Classification

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