Model-Based Clustering and Classification for Data Science: With Applications in R

by Gilles Celeux, Adrian E Raftery, Charles Bouveyron, et al.

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...

• Format: Hardcover
• Language: English
• ISBN: 110849420X
• ISBN13: 9781108494205
• Release Date: July 2019
• Publisher: Cambridge University Press
• Length: 446 Pages
• Weight: 2.40 lbs.
• Dimensions: 0.9" x 7.7" x 9.6"