Abstract
Clustering is a technique of grouping similar observations into smaller groups within the larger population. The resulting groups should be homogeneous, with each member of the cluster having more in common with members of the same cluster than with members of the other clusters. Cluster analysis is an exploratory data analysis tool which aims at sorting different objects into groups in a way to maximize the degree of association between objects in the same cluster. In this chapter several clustering techniques are explained. A simple example is used to explain the different clustering methods. Finally, clustering is applied to a subset of the automobile insurance data set.
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McCarthy, R.V., McCarthy, M.M., Ceccucci, W. (2022). Finding Associations in Data Through Cluster Analysis. In: Applying Predictive Analytics. Springer, Cham. https://doi.org/10.1007/978-3-030-83070-0_8
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DOI: https://doi.org/10.1007/978-3-030-83070-0_8
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