Image from Google Jackets

Data Analysis, Classification, and Related Methods [electronic resource] / edited by Henk A.L. Kiers, Jean-Paul Rasson, Patrick J.F. Groenen, Martin Schader.

Contributor(s): Material type: TextTextSeries: Studies in Classification, Data Analysis, and Knowledge OrganizationPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2000Edition: 1st ed. 2000Description: XIV, 428 p. 38 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642597893
Other title:
  • Proceedings of the 7th Conference on the International Federation of Classification Societies (IFCS-2000), University of Namur, Belgium, 11-14 July, 2000
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519.5
LOC classification:
  • QA276-280
Online resources:
Contents:
Cluster Analysis -- Discrimination, Regression Trees, and Data Mining -- Multivariate and Multidimensional Data Analysis -- Data Science -- Symbolic Data Analysis.
In: Springer Nature eBookSummary: This volume contains a selection of papers presented at the Seven~h Confer­ ence of the International Federation of Classification Societies (IFCS-2000), which was held in Namur, Belgium, July 11-14,2000. From the originally sub­ mitted papers, a careful review process involving two reviewers per paper, led to the selection of 65 papers that were considered suitable for publication in this book. The present book contains original research contributions, innovative ap­ plications and overview papers in various fields within data analysis, classifi­ cation, and related methods. Given the fast publication process, the research results are still up-to-date and coincide with their actual presentation at the IFCS-2000 conference. The topics captured are: • Cluster analysis • Comparison of clusterings • Fuzzy clustering • Discriminant analysis • Mixture models • Analysis of relationships data • Symbolic data analysis • Regression trees • Data mining and neural networks • Pattern recognition • Multivariate data analysis • Robust data analysis • Data science and sampling The IFCS (International Federation of Classification Societies) The IFCS promotes the dissemination of technical and scientific information data analysis, classification, related methods, and their applica­ concerning tions.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)

Cluster Analysis -- Discrimination, Regression Trees, and Data Mining -- Multivariate and Multidimensional Data Analysis -- Data Science -- Symbolic Data Analysis.

This volume contains a selection of papers presented at the Seven~h Confer­ ence of the International Federation of Classification Societies (IFCS-2000), which was held in Namur, Belgium, July 11-14,2000. From the originally sub­ mitted papers, a careful review process involving two reviewers per paper, led to the selection of 65 papers that were considered suitable for publication in this book. The present book contains original research contributions, innovative ap­ plications and overview papers in various fields within data analysis, classifi­ cation, and related methods. Given the fast publication process, the research results are still up-to-date and coincide with their actual presentation at the IFCS-2000 conference. The topics captured are: • Cluster analysis • Comparison of clusterings • Fuzzy clustering • Discriminant analysis • Mixture models • Analysis of relationships data • Symbolic data analysis • Regression trees • Data mining and neural networks • Pattern recognition • Multivariate data analysis • Robust data analysis • Data science and sampling The IFCS (International Federation of Classification Societies) The IFCS promotes the dissemination of technical and scientific information data analysis, classification, related methods, and their applica­ concerning tions.

There are no comments on this title.

to post a comment.

Powered by Koha