Decision Tree´s Pruning Algorithm Based on Deficient Data Sets

ID3 algorithm is a decision tree induction algorithm, but its pruning method (EEP) is an ineffective method when the data sets are deficient, uncertain. In this paper we analyze and study the ID3 algorithm and its pruning methods, then improve on EEP algorithm, and put forward a new pruning method - IEEP which can prune more unknown nodes and can not fall algorithm accuracy rate. We present experimental results that show the method performs better than alternatives, especially when dealing with deficient data sets.