Paul D. McNicholas

Mixture Model-Based Classification (eBook, PDF)

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 236
• Erscheinungstermin: 4. Oktober 2016
• Englisch
• ISBN-13: 9781482225679
• Artikelnr.: 46757646

Autorenporträt

Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. His research focuses on the use of mixture model-based approaches for classification, with particular attention to clustering applications, and he has published extensively within the field. He is an associate editor for several journals and has served as a guest editor for a number of special issues on mixture models.