Research on decision tree improvement by Bayes logic
Weidong Cai · 2003
Decision tree is in common used on forecast, decision and data mining. In this paper, the growing process of decision trees is analyzed, and an improving method of decision tree by integrating with Bayes logic is proposed to overcome the defects from decision tree over-growth in current methods. In this method, the storage structure of data and growing technology of decision tree are given, and the split condition at each node of decision trees is judged according to rules produced in data mining. It can restrict the over-growth of decision tree and also decide the optimal route, thereby obviously promote the efficiency of decision-making.