A Method of Dealing with Numeric Attribute Based on Sample Distribution

Abstract

In order to improve the predictive accuracy of inductive learning, a heavy analysis about the demerit of C4.5 in dealing with numeric attribute is given. By the method of estimating the probability distribution of the training samples, a new and simple method of dealing with numeric attribute is proposed in this paper. Experimental results of UCI data sets show that the proposed method has an excellent performance on accuracy issue and faster computing speed than C4.5 algorithm.