Classification models classify input data into categories. Typical applications include medical imaging, speech recognition, and credit scoring.
Classification is the process of finding a model (or function) that describes and distinguishes data classes or concepts, for the purpose of being able to use the model to predict the class of objects whose class label is unknown. The derived model is based on the analysis of a set of training data (data objects whose class label is known). The derived model can take the form of classification (IF-THEN) rules, decision trees, mathematical formulae, or neural networks.