Titlebook: Unsupervised Classification; Similarity Measures, Sanghamitra Bandyopadhyay,Sriparna Saha Textbook 2013 Springer-Verlag Berlin Heidelberg 2

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Some Line Symmetry Distance-Based Clustering Techniques,o the first principal axis of a cluster. It is applicable for data sets of any number of dimensions. A genetic clustering technique using this line symmetry-based distance is also described. Experimental results show the efficacy of this technique over other competing ones.

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Clustering Algorithms, thereafter formulated as one of optimization and some evolutionary clustering techniques are described. Finally it is shown how clustering can be posed as a multiobjective optimization problem and some recently developed multiobjective clustering techniques are described in brief.

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Introduction, and the research issues, challenges and application domains. The chapter starts with a brief overview of the different data types e.g., binary, categorical, ordinal and quantitative, with several examples. Thereafter the steps in automatic machine recognition of patterns are described in detail, in

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Some Single- and Multiobjective Optimization Techniques,the single and multiobjective optimization problems are provided. Different concepts related to multiobjective optimization are described in detail. Two popular metaheuristics, namely genetic algorithms and simulated annealing, are elaborately discussed. Several existing multiobjective evolutionary

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Clustering Algorithms,-medoid, and fuzzy .-means are described. This is followed by a discussion on some distribution-based clustering techniques, namely expectation maximization. Hierarchical clustering techniques, like single linkage, average linkage and complete linkage, and density-based clustering techniques, like D

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Point Symmetry-Based Distance Measures and Their Applications to Clustering,have been developed. The definitions of these measures and their advantages and disadvantages are elaborately described in the first part of this chapter. In the second part, a recently developed genetic algorithm-based clustering technique, named GAPS, that uses a symmetry-based distance for assign

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A Validity Index Based on Symmetry: Application to Satellite Image Segmentation,x, is described in detail, and an intuitive explanation of how the different components of .-index compete with each other to identify a proper clustering is provided. A mathematical justification of the new index is derived by establishing its relationship with the well-known Dunn’s index. Experime