Mixture Model-Based Classification - McNicholas, Paul D
134,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
payback
67 °P sammeln
  • Gebundenes Buch

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.

Andere Kunden interessierten sich auch für
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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.