Publisher Summary
This chapter presents the basic concepts and methods of cluster analysis. The requirements of clustering methods for massive amounts of data and various applications are studied. Several basic clustering techniques are discussed organized into the following categories: partitioning methods, hierarchical methods, density-based methods, and grid-based methods). Evaluation process for clustering methods is also discussed. A cluster is a collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other clusters. The process of grouping a set of physical or abstract objects into classes of similar objects is called clustering. Clustering is the process of grouping a set ...
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