A label is a category into which a record falls, usually in the context of predictive modeling. Label, class and category are different names for discrete values of a target (outcome) variable. “Label” typically has the added connotation that the label is something applied by a human to model-training data, so that a predictive modeling method can learn to assign labels to similar unlabeled data. For example, a paralegal might label a sample of documents as “relevant” and “not-relevant” so that a machine learning algorithm might learn from the sample, and apply the same labels to other, unlabeled data.
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