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

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...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Bandyopadhyay, Sanghamitra (Auteur), Saha, Sriparna (Auteur)
Collectivité auteur: SpringerLink (Online service)
Format: Électronique eBook
Langue:Inglés
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Édition:1st ed. 2013.
Sujets:
Artificial intelligence.
Bioinformatics.
Computer networks .
Artificial Intelligence.
Computational and Systems Biology.
Computer Communication Networks.
Accès en ligne:Texto Completo
Table des matières:
  • 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.

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