Unsupervised Learning
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_976
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Unsupervised learning refers to any machine learning process that seeks to learn structure in the absence of either an identified output (cf. supervised learning) or feedback (cf. reinforcement learning). Three typical examples of unsupervised learning are clustering, association rules, and self-organizing maps.
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© Springer Science+Business Media New York 2017