Predict Classifications Based on Continuous Variables
Discriminant analysis predicts membership in a group or category based on observed values of several continuous variables. Specifically, discriminant analysis predicts a classification (X) variable (nominal or ordinal) based on known continuous responses (Y). The data for a discriminant analysis consist of a sample of observations with known group membership together with their values on the continuous variables.
For example, you might attempt to classify loan applicants into three credit risk categories (X): good, moderate, or bad. You might use continuous variables such as current salary, years in current job, age, and debt burden, (Ys) to predict an individual’s ...