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Overview on Techniques in Cluster Analysis

  • Itziar Frades
  • Rune Matthiesen
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 593)

Abstract

Clustering is the unsupervised, semisupervised, and supervised classification of patterns into groups. The clustering problem has been addressed in many contexts and disciplines. Cluster analysis encompasses different methods and algorithms for grouping objects of similar kinds into respective categories. In this chapter, we describe a number of methods and algorithms for cluster analysis in a stepwise framework. The steps of a typical clustering analysis process include sequentially pattern representation, the choice of the similarity measure, the choice of the clustering algorithm, the assessment of the output, and the representation of the clusters.

Key words

Clustering algorithm feature selection feature extraction similarity measure cluster tendency cluster validity cluster stability relevance networks dendrogram 

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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Itziar Frades
    • 1
  • Rune Matthiesen
    • 2
  1. 1.BioinformaticsParque Technológico de BizkaiaDerioSpain
  2. 2.Instituto de Patologia e Imunologia Molecular da Universidad do Porto – IPATIMUPPortoPortugal

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