Supervised learning
Supervised learning is the automatic learning task simpler and better known. It is based on a number of preclassified examples, in which, namely, is known a prior the category to which each of the inputs used as examples should belong. In this case, the crucial issue is the problem of generalization. After the analysis of a sample (often small) of examples, the system should produce a model that should work well for all possible inputs.
The set consists of labeled data, that is, objects and their associated classes. This set of labeled examples, therefore, constitutes the training set.
Most of the supervised learning algorithms share one characteristic: the training is performed by the minimization of a particular loss ...
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