Research and Improvement of Decision Trees Algorithm

Decision tree is a key classification method in data mining.Firstly,based on the research and comparison of several classic decision trees algorithms,an improved decision tree algorithm based on metric is proposed in this paper.In practice,this kind of decision trees combines linear classifier and decision trees.The experimental result indicates that the decision trees based on this method can effectively reduce the decision trees level,which enhance classified efficiency of the decision trees.MBDT classified experiment results demonstrate the correctness and availability of the above conclusions.