Unsupervised Classification Similarity Measures, Classical and Metaheuristic Approaches, and Applications /

• Main Authors: Bandyopadhyay, Sanghamitra. (Author), Saha, Sriparna. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Subjects: Computer science.; Information systems.; Artificial intelligence.; Bioinformatics.; Computer Science.; Artificial Intelligence (incl. Robotics).; Computational Biology/Bioinformatics.; Information Systems and Communication Service.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-32451-2

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...

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.