Unsupervised Classification

Similarity Measures, Classical and Metaheuristic Approaches, and Applications

  • Sanghamitra Bandyopadhyay
  • Sriparna Saha

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 1-16
  3. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 17-58
  4. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 59-73
  5. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 75-92
  6. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 93-123
  7. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 125-163
  8. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 165-195
  9. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 197-215
  10. Sanghamitra Bandyopadhyay, Sriparna Saha
    Pages 217-243
  11. Back Matter
    Pages 245-262

About this book


Clustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex problem as a variety of similarity and dissimilarity measures exist in the literature.

This is the first book focused on clustering with a particular emphasis on symmetry-based measures of similarity and metaheuristic approaches. The aim is to find a suitable grouping of the input data set so that some criteria are optimized, and using this the authors frame the clustering problem as an optimization one where the objectives to be optimized may represent different characteristics such as compactness, symmetrical compactness, separation between clusters, or connectivity within a cluster. They explain the techniques in detail and outline many detailed applications in data mining, remote sensing and brain imaging, gene expression data analysis, and face detection.

The book will be useful to graduate students and researchers in computer science, electrical engineering, system science, and information technology, both as a text and as a reference book. It will also be useful to researchers and practitioners in industry working on pattern recognition, data mining, soft computing, metaheuristics, bioinformatics, remote sensing, and brain imaging.


Bioinformatics Brain imaging Clustering Data mining Facial recognition Imaging Metaheuristics Multiobjective optimization Optimization Similarity Symmetry

Authors and affiliations

  • Sanghamitra Bandyopadhyay
    • 1
  • Sriparna Saha
    • 2
  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia
  2. 2.Dept. of Computer Science, and EngineeringIndian Institute of TechnologyPatnaIndia

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-32450-5
  • Online ISBN 978-3-642-32451-2
  • Buy this book on publisher's site
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