Multi-path Decision Tree

摘要：

　　Decision trees are well-known and established models for classification and regression.In this paper,we propose multi-path decision tree algorithm (MPDT).Different from traditional decision tree where the path of each record is deterministic and exclusive,a record can trace several paths simultaneously in multi-path decision tree so that it has the effect of ensemble classifiers with only one classifier.Local class information gain is the value of class information (entropy or Gini,etc) given the value of an attribute relative to class information unsupervised.We examine the MPDT on a random selection of 26 benchmark data sets from the UCI repository and compared it with Bagging,AdaBoost and C4.5.The results note that MPDT has better performance.

关键词： component formatting style styling insert

作者: Huaping Guo Ming Fan

作者单位: School of Information Engineering,ZhengZhou University,P.R.China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 1412-1414

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）