Non-probabilistic classification

Gower, John C. and Ross, Gavin J. S. (1998). Non-probabilistic classification. In: Rizzi, Alfredo; Vichi, Maurizio and Bock, Hans Hermann eds. Advances in Data Science and Classification. New York, NY U.S.: Springer, pp. 21–28.

DOI: https://doi.org/10.1007/978-3-642-72253-0_3

URL: http://www.springer.com

Abstract

About the book:
The book provides new developments in classification and data analysis, and presents new topics which are of central interest to modern statistics. In particular, these include classification theory, multivariate data analysis, multi-way data, proximity structure analysis, new software for classification and data analysis, and applications in social, economic, medical and other sciences. For many of these topics, this book provides a systematic state of the art written by top researchers in the world. This book will serve as a helpful introduction to the area of classification and data analysis for research workers and support the transfer of new advances in data science and classification to a wide range of applications.

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About

• Item ORO ID
• 24101
• Item Type
• Book Section
• ISBN
• 3-540-64641-8, 978-3-540-64641-9
• Extra Information
• proceedings of the 6th Conference of the International Federation of Classification Societies (IFCS-98), Università "La Sapienza", Rome, 21-24 July, 1998
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 1998 Springer
• Depositing User
• Sarah Frain