Discriminant analysis identifies clusters of attributes on which objects differ, similar to factor analysis

Question

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Discriminant analysis is used to predict a categorical dependent variable by one or more continuous or binary independent variables; it does not identify clusters of attributes but rather determines which variables discriminate between different categories of the dependent variable. Factor analysis, on the other hand, is used to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables.

Discriminant Analysis Identifies Clusters of Attributes on Which Objects Differ