Unsupervised learning: The algorithm trains on unlabeled data. The goal of these algorithms is to explore the data and find some structure within. For example, using these algorithms, the presidential campaigns can identify segments of voters with similar attributes who can then be treated similarly in the campaign by customizing campaign efforts for each group. The most widely used unsupervised learning algorithms are Cluster Analysis and Market Basket Analysis.
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