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. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and realtime applications. The book provides clear guidance for the varying needs of both applications, describing scenarios in which accuracy and speed are the primary goals. Robust Cluster Analysis and Variable Selection includes all of the important theoretical details, and covers the key probabilistic models, robustness issues, optimization algorithms, validation techniques, and variable selection methods. The book illustrates the different methods with simulated data and applies them to realworld data sets that can be easily downloaded from the web. This provides you with guidance in how to use clustering methods as well as applicable procedures and algorithms without having to understand their probabilistic fundamentals.
About Gunter Ritter
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.Details Book
Author  :  Gunter Ritter 
Publisher  :  Chapman 
Data Published  :  04 September 2014 
ISBN  :  1439857962 
EAN  :  9781439857960 
Format Book  :  PDF, Epub, DOCx, TXT 
Number of Pages  :  392 pages 
Age +  :  15 years 
Language  :  English 
Rating  : 
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