Unsupervised Classification (Record no. 52621)

000 -LEADER
fixed length control field 03627nam a22005055i 4500
001 - CONTROL NUMBER
control field 978-3-642-32451-2
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200420221251.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121212s2013 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783642324512
-- 978-3-642-32451-2
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Bandyopadhyay, Sanghamitra.
245 10 - TITLE STATEMENT
Title Unsupervised Classification
Sub Title Similarity Measures, Classical and Metaheuristic Approaches, and Applications /
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVIII, 262 p.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Saha, Sriparna.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-32451-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2013.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computers.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Bioinformatics.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Biology/Bioinformatics.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information Systems and Communication Service.
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-- ZDB-2-SCS

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