An Improved Decision Tree Algorithm Based on Dispersed Degree
Yubin Guo · Modern Electronics Technique · 2006
In data mining,decision tree algorithm is a key research direction.ID3 method is a famous decision tree algorithm,among this kind of algorithm,the calculation of information gain depends on the characteristic of characteristic value more in figure,it is not so very rational.For this reason,the article improves ID3 algorithm in terms of dispersed degree,through the contrast experiment of two kinds of algorithms,proves that utilizes the algorithm after improving to excavate the categorized rule,not only has improved the correct rate classified,but also very highefficient.