Improved algorithm of C4.5 decision tree on the arithmetic average optimal selection classification attribute

Abstract

To try to decrease the preference of the attribute values for information gain and information gain ratio, in the paper, the authors puts forward a improved algorithm of C4.5 decision tree on the selection classification attribute. The basic thought of the algorithm is as follows: Firstly, computing the information gain of selection classification attribute, and then get an attribute of the information gain which is higher than the average level; Secondly, computing separately the arithmetic average value of the information gain ratio and information gain of the attribute, and then select the biggest attribute of the average value and set up a branch decision; Finally, to use recursive method to build a decision tree. The experiment shows that this method is applicable and effective.