Cluster Analysis

  • S. SreejeshEmail author
  • Sanjay Mohapatra
  • M. R. Anusree


Cluster analysis is a group of multivariate techniques whose major objective is to combine observations/object/cases into groups or clusters, such that each group or cluster formed is homogeneous or similar with respect to some certain characteristics and these groups should be different from other groups with respect to same characteristics. In cluster analysis, the researcher can classifies objects, such as respondents, products or other entities and cases or events, based on a set of selected variables or characteristics. Cluster analysis works based on certain set of variables, called “Cluster variate”, which form the basis for comparing the objects in the cluster analysis. In cluster analysis, the selection of cluster variate is very important, because in cluster analysis the focus is for comparing the objects in each cluster based on variate, rather than the estimation of the variate itself. This difference makes cluster analysis different from other multivariate techniques. Therefore, the researcher’s definition of the cluster variate plays a crucial role in cluster analysis.


Cluster Analysis Hierarchical Cluster Analysis Cluster Solution Cluster Variate Cluster Centroid 
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 International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.IBS HyderabadIFHE UniversityHyderabadIndia
  2. 2.Xavier Institute of ManagementBhubaneswarIndia
  3. 3.Department of StatisticsUniversity of KeralaTrivandrumIndia

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