Wikipedia Feature learning
techniques (mostly unsupervised learning algorithms) that learn a feature: a transformation of raw data input to a representation that can be effectively exploited in machine learning tasks (= aim at discovering better representations of the inputs provided during training. Classical examples include principal components analysis and cluster analysis. Representation learning algorithms often attempt to preserve the information in their input but transform it in a way that makes it useful)
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