Title Statements
- Full title :Mixture model-based classification / Paul D. McNicholas, McMaster University, Ontario, Canada.
Edition Statements
- Publication Date:2017
Publication Statements
- Publisher(s):CRC Press, Taylor & Francis Group
- Place of Publication:Boca Raton
- Language:eng
- Publication Date:2017
Notes
"A Chapman & Hall book."
The Physical Object
- Description:xxiv, 212 pages : : illustrations ; : 24 cm
Edition Identifiers
- ISBN:9781482225662, 1482225662
- oclc:ocn908375987
- LC Classification:QA278.4
- Dewey Decimal:519.5/35
Table of Contents
Machine generated contents note: 1.Introduction -- 1.1.Classification -- 1.2.Finite Mixture Models -- 1.3.Model-Based Clustering, Classification, and Discriminant Analysis -- 1.4.Comparing Partitions -- 1.5.R Packages -- 1.6.Datasets -- 1.7.Outline of the Contents of This Monograph -- 2.Mixtures of Multivariate Gaussian Distributions -- 2.1.Historical Development -- 2.2.Parameter Estimation -- 2.2.1.Model-Based Clustering -- 2.2.2.Model-Based Classification -- 2.2.3.Model-Based Discriminant Analysis -- 2.2.4.Initialization via Deterministic Annealing -- 2.2.5.Stopping Rules -- 2.3.Gaussian Parsimonious Clustering Models -- 2.4.Model Selection -- 2.5.Merging Gaussian Components -- 2.6.Illustrations -- 2.6.1.x2 Data -- 2.6.2.Banknote Data -- 2.6.3.Female Voles Data -- 2.6.4.Italian Olive Oil Data -- 2.7.Comments -- 3.Mixtures of Factor Analyzers and Extensions -- 3.1.Factor Analysis -- 3.1.1.The Model -- 3.1.2.An EM Algorithm for the Factor Analysis Model
Note continued: 3.1.3.Woodbury Identity -- 3.1.4.Comments -- 3.2.Mixture of Factor Analyzers -- 3.3.Parsimonious Gaussian Mixture Models -- 3.3.1.A Family of Eight Models -- 3.3.2.Parameter Estimation -- 3.3.3.Comments -- 3.4.Expa…
Subjects
Writers
No reviews yet. Be the first to rate this work.
Files & Downloads
-
Mixture model-based classification -- (.pdf)
PDF · 11.1 MB · updated
Rate & Review