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Automatic Clustering Based on Cluster Nearest Neighbor Distance (CNND) Algorithm

  • Arghya Sur
  • Aritra Chowdhury
  • Jaydeep Ghosh Chowdhury
  • Swagatam Das
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 199)

Abstract

This article describes a simple and fast algorithm that can automatically detect any number of well separated clusters, which may be of any shape e.g. convex and/or non-convex. This is in contrast to most of the existing clustering algorithms that assume a value for the number of clusters and/or a particular cluster structure. This algorithm is based on the principle that there is a definite threshold in the intra-cluster distances between nearest neighbors in the same cluster. Promising results on both real and artificial datasets have been included to show the effectiveness of the proposed technique.

Keywords

Cluster nearest Neighbour Clustering Automatic Clustering Various shaped clusters 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Arghya Sur
    • 1
  • Aritra Chowdhury
    • 1
  • Jaydeep Ghosh Chowdhury
    • 1
  • Swagatam Das
    • 2
  1. 1.Dept. of Electronics and Telecomunication EnggJadavpur UniversityKolkataIndia
  2. 2.Electronics and Computer Sciences UnitIndian Statistical InstituteKolkataIndia

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