Classification methods split observations within a data set into a set of distinct classes by assigning class labels. Because classification is a supervised machine learning method, the training stage requires a data set that consists of both feature vectors and class labels that indicate membership of observations in a particular class. The prediction stage takes a data set (labeled or unlabeled) on input and assigns a class label to each observation.

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