Linear Versus Quadratic Multivariate Classification.

A linear classification rule (used with equal covariance matrices) was contrasted with a quadratic rule (used with unequal covariance matrices) for accuracy of internal and external classification. The comparisons were made for seven situations which resulted from combining conditions (equal and unequal covariance matrices, and two and three criterion groups) for different sets of real data. For the internal analysis the quadratic rule was superior to the linear rule in all seven situations. For the external analysis the linear rule was nearly as good as or superior to the quadratic rule in all seven situations.