2. Classical" supervised learning techniques
Supervised learning corresponds to algorithms using data (examples) that are a set of N pairs (input vector , desired value y n ), with n varying from 1 to N, and where each is a vector of dimension d. What they have in common is that they seek a function h from in
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Classical" supervised learning techniques
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