One strategy for dealing with an excessive number of cases is to identify groups that are similar, a process known as clustering or unsupervised learning, since we have to learn about these groups and are not told in advance that they exist. Finding these fairly homogeneous clusters can be an end in itself, for example by identifying groups of people with similar likes and dislikes, which then can be characterized, given a label, and algorithms built for classifying future cases. The clusters that have been identified can then be fed appropriate film recommendations, advertisements, or
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Clustering and feature engineering
