Book contents
- Frontmatter
- Contents
- Preface
- Notation
- 1 Introduction
- 2 Mathematical Foundation
- 3 Supervised Machine Learning (in a Nutshell)
- 4 Feature Extraction
- DISCRIMINATIVE MODELS
- GENERATIVE MODELS
- 10 Overview of Generative Models
- 11 Unimodal Models
- 12 Mixture Models
- 13 Entangled Models
- 14 Bayesian Learning
- 15 Graphical Models
- APPENDIX
- Bibliography
- Index
12 - Mixture Models
from GENERATIVE MODELS
Published online by Cambridge University Press: 18 November 2021
Book contents
- Frontmatter
- Contents
- Preface
- Notation
- 1 Introduction
- 2 Mathematical Foundation
- 3 Supervised Machine Learning (in a Nutshell)
- 4 Feature Extraction
- DISCRIMINATIVE MODELS
- GENERATIVE MODELS
- 10 Overview of Generative Models
- 11 Unimodal Models
- 12 Mixture Models
- 13 Entangled Models
- 14 Bayesian Learning
- 15 Graphical Models
- APPENDIX
- Bibliography
- Index
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- Information
- Machine Learning FundamentalsA Concise Introduction, pp. 257 - 290Publisher: Cambridge University PressPrint publication year: 2021