Robust Cluster Analysis and Variable Selection

Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. This book presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50

List of contents

Introduction. Mixture and Classification Models and Their Likelihood Estimators. Robustification by Trimming. Algorithms. Favorite Solutions and Cluster Validation. Variable Selection in Clustering. Applications. Appendices. Bibliography. Index.

About the author

Dr. Gunter Ritter is an emeritus professor in the Department of Mathematics and Computer Science at the University of Passau. He is the author and coauthor of numerous research papers in scientific journals in the areas of measure theory, probability theory, queuing theory, statistics, pattern and image recognition, and Fourier analysis. He is a member of the International Federation of Classification Societies and its German branch GfKl as well as the German Mathematical Society.

Summary

Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. This book presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50

Product details

• Authors: Gunter Ritter, Ritter Gunter
• Publisher: Taylor and Francis
• Languages: English
• Product format: Paperback / Softback
• Released: 14.10.2024
• EAN: 9781032920665
• ISBN: 978-1-032-92066-5
• No. of pages: 394
• Weight: 453 g
• Illustrations: schwarz-weiss Illustrationen
• Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Data Mining, MATHEMATICS / Probability & Statistics / General, computer science, Probability & statistics, Probability and statistics, COMPUTERS / Data Science / Data Analytics