Discrimination with Mixed Binary and Continuous Data

SUMMARY This paper consists of a case study in the use of different methods of Discriminant analysis. Methods used include Fisher's Linear discriminant function, various modifications of this technique, Logistic discrimination and Kernel methods using jack-knife maximum likelihood. These methods are applied on two sets of data. Their success is compared using the proportions misclassified, estimated by the leaving-one-out method where possible.