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Clustering

  • Max Bramer
Part of the Undergraduate Topics in Computer Science book series (UTICS)

Abstract

This chapter continues with the theme of extracting information from unlabelled data. Clustering is concerned with grouping together objects that are similar to each other and dissimilar to objects belonging to other clusters.

There are many methods of clustering. Two of the most widely used, k-means clustering and hierarchical clustering are described in detail.

Keywords

Distance Matrix Single Cluster Unlabelled Data Agglomerative Hierarchical Cluster Close Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Max Bramer
    • 1
  1. 1.School of ComputingUniversity of PortsmouthPortsmouthUK

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