Discriminant Analysis

Discriminant Analysis: Pattern recognition

Discriminant analysis is a technique for classifying a set of observations into predefined classes. The purpose is to determine the class of an observation based on a set of variables known as predictors or input variables. The model is built based on a set of observations for which the classes are known. This set of observations is sometimes referred to as the training set.

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Cluster Analysis: Associative memories

Isn't discriminant analysis the same as cluster analysis?
No. In discriminant analysis the groups (clusters) are determined beforehand and the object is to determine the linear combination of independent variables which best discriminates among the groups. In cluster analysis the groups (clusters) are not predetermined and in fact the object is to determine the best way in which cases may be clustered into groups

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