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Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm is evaluated by its ability to generalize, i.e., to extend this mapping accurately to new data that is commonly referred to as the test data. Good generalization depends crucially on the quality of the training set. Because...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.