Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)

Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan; Raftery, Adrian E.

ISBN 10: 110849420X / ISBN 13: 9781108494205

Published by Cambridge University Press, 2019

About this Item

Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Seller Inventory # S_348802842

Bibliographic Details

• Title: Model-Based Clustering and Classification for Data Science: With Applications in R (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)
• Publisher: Cambridge University Press
• Publication Date: 2019
• Language: English
• ISBN 10: 110849420X
• ISBN 13: 9781108494205
• Binding: hardcover
• Condition: Good

About this title

Synopsis

Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding...

More