Research on Decision Tree Classification Algorithms

ID3 algorithm tends to choose the attributes of more values as the splitting attributes.Aiming at the problem,this paper introduces two parameters including attribute importance and number of attribute values to improve the existed formula of information gain of ID3 algorithm.This contributes to enhancing the importance of the critical attributes with fewer values and making the algorithm better reflect the actual decision-making situation.According to the properties of the convex function,it simplifies the calculating formula of information entropy to improve the efficiency of constructing a decision tree.A concrete example is given to describe the specific application of improved algorithm,and the result shows that it is more efficient than the original algorithm.