Abstract
The term “cluster” is synonymous with both “group” as a noun and “classify” as a verb. Cluster analysis , which is also simply called clustering , generally refers to the procedures for computationally classifying (i.e., clustering) individuals into groups (i.e., clusters) so that similar individuals are classified into the same group and mutually dissimilar ones are allocated to different groups. There are various procedures for performing cluster analysis. One of the most popular of these, called k-means clustering (KMC) , which was first presented by MacQueen (1967), is introduced here.
The original version of this chapter was revised: Belated corrections have been incorporated. The erratum to this chapter is available at https://doi.org/10.1007/978-981-10-2341-5_17
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© 2016 Springer Nature Singapore Pte Ltd.
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Adachi, K. (2016). Cluster Analysis. In: Matrix-Based Introduction to Multivariate Data Analysis. Springer, Singapore. https://doi.org/10.1007/978-981-10-2341-5_7
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DOI: https://doi.org/10.1007/978-981-10-2341-5_7
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