ABSTRACT
Several clustering algorithms have been proposed that deal with grouping a data set, that which has not been previously grouped, into a number of groups or clusters of similar data points. Clustering a data set is also known as labeling the data set, since each data point is assigned a label, i.e., a cluster id. The following clustering algorithms are described: hierarchical clustering, k-means clustering, fuzzy c-means model, Gaussian mixture decomposition, and DBSCAN. A set of exercises and a clustering project is given at the end of the Chapter.
