Most clustering algorithms are unsupervised, simply, taking groups of values and associating items based on similarity of attributes. Of cousre, the idea of what similarty means for a oaetickar data set does have to be specified by the algorithm user, or is a fixed feature of the algorithm. Examples include k-means and self-organising maps.
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