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Unsupervised Learning Algorithm

A learning algorithm which learns unlabeled data. This algorithms family is usually divided into 2 groups: 1) Clustering - a problem family where the algorithm aims to discover the inherent groupings in the data, Example: grouping customers by purchasing behavior. Popular algorithm in this family is k-means. 2) Association - rule learning problem where the algorithm aims to discover rules that describe large portions of the data, Example: people that buy X also tend to buy Y.

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