Clustering is a unsupervised learning technology which is required in many fields like pattern recognition. Given a predefined similarity metric, clustering divides a data set into a number of classes so that data points from one class have more similarity than data from different classes.

Some popular algorithm are: k-means, expectation maximization and Gibbs alogrithm, referring to:

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