A New Structuring Method of Decision Tree
Xu Linzhang, Qiang Zhao, Zhang Yanning · 2008
Decision tree is a common classification algorithm, but this classic algorithm shows low efficiency when dealing with massive data structure decision tree. This paper presents a new approach to structuring decision tree. The split calculation of training units in classic algorithm is taken the place by FP Tree path sets. This method can improve the efficiency of decision tree with the presupposition that the results are the same with the classic algorithm. This method has been testified its validity and superiority by experiments.