Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
3
views
0
references
Top references
cited by
14
Cite as...
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
1,683
similar
All similar
Record
: found
Abstract
: not found
Book
: not found
Model-Based Clustering and Classification for Data Science : With Applications in R
monograph
Author(s):
Charles Bouveyron
,
Gilles Celeux
,
T. Brendan Murphy
,
Adrian E. Raftery
Publication date
(Online):
June 14 2019
Publisher:
Cambridge University Press
Read this book at
Publisher
Buy book
Review
Review book
Invite someone to review
Bookmark
Cite as...
There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Value-based Healthcare
Author and book information
Book
ISBN (Electronic):
9781108644181
ISBN (Print):
9781108494205
Publication date (Online):
June 14 2019
Publication date (Print):
July 31 2019
DOI:
10.1017/9781108644181
SO-VID:
ef2c6368-02d2-4d09-85ac-02afdfe8b50a
History
Data availability:
Comments
Comment on this book
Sign in to comment
Book chapters
pp. 1
Introduction
pp. 15
Model-based Clustering: Basic Ideas
pp. 79
Dealing with Difficulties
pp. 109
Model-based Classification
pp. 134
Semi-supervised Clustering and Classification
pp. 163
Discrete Data Clustering
pp. 199
Variable Selection
pp. 217
High-dimensional Data
pp. 259
Non-Gaussian Model-based Clustering
pp. 292
Network Data
pp. 331
Model-based Clustering with Covariates
pp. 351
Other Topics
pp. 386
Bibliography
pp. 415
Author Index
pp. 423
Subject Index
Similar content
1,683
bibliometrix : An R-tool for comprehensive science mapping analysis
Authors:
Corrado Cuccurullo
,
Massimo Aria
Natrix2 – Improved amplicon workflow with novel Oxford Nanopore Technologies support and enhancements in clustering, classification and taxonomic databases
Authors:
Aman Deep
,
Dana Bludau
,
Marius Welzel
…
Staggering behavior of the low lying excited states of even-even nuclei in a Sp(4,R) classification scheme
Authors:
,
,
See all similar
Cited by
12
Clustering-based simultaneous forecasting of life expectancy time series through Long-Short Term Memory Neural Networks
Authors:
Susanna Levantesi
,
Andrea Nigri
,
Gabriella Piscopo
Finite Mixtures of ERGMs for Modeling Ensembles of Networks
Authors:
Fan Yin
,
Weining Shen
,
Carter Butts
Unsupervised Multi-View K-Means Clustering Algorithm
Authors:
Miin-Shen Yang
,
Ishtiaq Hussain
See all cited by