The Separability of Split Value Criterion
نویسنده
چکیده
The Separability of Split Value (SSV) criterion is a simple and efficient tool for building classification trees and extraction of logical rules. It deals with both continuous and discrete features describing data vectors and requires no user interaction in the learning process. Extensions of methods based on this criterion are presented. They aim at improvement of reliability and efficiency of the methods and extension of their applications area. Good results for several benchmark datasets were obtained.
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