A Decision Tree Algorithm Based on MMTD
ZHU Lizhi
Abstract：decision tree is a kind of commonly used classification algorithm,since the ID3 algorithm has been related to the personnel to improve the algorithm,which appeares a variety of decision tree algorithm. When the decision tree is generated,the re?cursive algorithm is used to split the nodes of the decision tree. If the information gain of nodes is bigger,the probability of node splitting is greater. The ID3 algorithm and C4.5 algorithm in the information gain becomes an important basis for the node is split,so according to characteristics of the decision tree node split when the information gain function,this paper presents another algorithm to measure the size of the information gain,the algorithm with measure formula and the core algorithm——MMTD algorithm. The in?novation of this paper lies in MMTD algorithm in decision tree were used for the first time,and in the MMTD as the basis and the core of the algorithm is to achieve the measure of the size of the information gain.
Keywords：MMTDdecision treeinformation entropyinformation gainID3 algorithm
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 839-843 )