Diskriminant rules based on distances

Rok, strany: 1996, 289 - 296

Optimal classification rules based on linear functions which maximize and Chernoff distance, or the Morisita distance, or the Kullback-Leibler distance are studied here. We obtain an expression for the optimal linear discriminant function and show that the resulting linear procedure belongs to the Anderson-Bahadur admissible class. For the comparison of discriminant rules we use some index which is the measure of the accuracy of a given class of discriminant procedures.

ISO 690:

Krzyśko, M., Wołyński, W. 1996. Diskriminant rules based on distances. In Tatra Mountains Mathematical Publications, vol. 7, no.1, pp. 289-296. 1210-3195.

APA:

Krzyśko, M., Wołyński, W. (1996). Diskriminant rules based on distances. Tatra Mountains Mathematical Publications, 7(1), 289-296. 1210-3195.