Linear discriminant analysis is a supervised learning technique for classification that builds a predictive model for group membership. The model is composed of one or more discriminant functions based on linear combinations of predictor fields that provide the best discrimination between the groups. The functions are generated from a sample of instances or cases for which group membership is known. The functions can then be applied to new instances that have measurements for the predictors but have unknown group memberships.

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