Unsupervised Classification: Similarity Measures, Classical And Metaheuristic Approaches, And Applications by Sanghamitra BandyopadhyayUnsupervised Classification: Similarity Measures, Classical And Metaheuristic Approaches, And Applications by Sanghamitra Bandyopadhyay

Unsupervised Classification: Similarity Measures, Classical And Metaheuristic Approaches, And…

bySanghamitra Bandyopadhyay, Sriparna Saha

Paperback | January 29, 2015

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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.

Prof. Sanghamitra Bandyopadhyay has many years of experience in the development of soft computing techniques. Among other awards and positions, she has received senior researcher Humboldt Fellowships, and she is a regular visitor to the DKFZ (German Cancer Research Centre) and to European and North American universities, collaborating ...
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Title:Unsupervised Classification: Similarity Measures, Classical And Metaheuristic Approaches, And…Format:PaperbackDimensions:262 pages, 23.5 × 15.5 × 0.17 inPublished:January 29, 2015Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3642428363

ISBN - 13:9783642428364

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Table of Contents

Chap. 1 Introduction.- Chap. 2 Some Single- and Multiobjective Optimization Techniques.- Chap. 3 SimilarityMeasures.- Chap. 4 Clustering Algorithms.- Chap. 5 Point Symmetry Based Distance Measures and their Applications to Clustering.- Chap. 6 A Validity Index Based on Symmetry: Application to Satellite Image Segmentation.- Chap. 7 Symmetry Based Automatic Clustering.- Chap. 8 Some Line Symmetry Distance Based Clustering Techniques.- Chap. 9 Use of Multiobjective Optimization for Data Clustering.- References.- Index.