4Vapnik V N. The Nature of Statistical Learning Theory [ M ]. New York: Springer- Verlag, 1995.
5Vapnik V N. Statistical Learning Theory [ M ]. J. Wiley, New York, 1998.
6Bastide R. Approaches in unifying Petri nets and the object - oriented approach [ C ]. In: the 1st workshop on object - oriented programming and models of Concurrency, Torino, Italy, 1995.
二级参考文献34
1Stone P,Veloso M.A layered approach to learning client behaviors in the RoboCup soccer server[J].Applied Artificial Intelligence(AAI),1998,12(2-3):165-187.
2Ankerst M,Elsen C,Ester M,et al.Visual classification:an interactive approach to decision tree construction[C].San Diego:In Proceedings of International Conference on Knowledge Discovery and Data Mining,1999.
3Fournier D,Cremilleux B.A quality index for decision tree pruning[J].Knowledge-based Systems,2002,15(1):37-43.
4Sebban M,Nock R,Chauchat J H,et al.Impact of learning set quality and size on decision tree performances[J].IJCSS,2000,1(1):85-105.
5Oates T,Jensen D.The effects of training set size on decision tree complexity[C].Nashville,Tennessee:Proc of the 14th International Conference on Machine Learning,1997.
6Brodley C E,Friedl M A.Identifying and eliminating mislabeled training instances[C].USA:Proceedings of the Thirteenth National Conference on Artificial Intelligence,1996.
7Elouedi Z,Mellouli K,Smets Ph.Decision trees using the belief function theory[C].Madrid,Spain:Proceedings of the Eighth International Conference IPMU,2000.
8Yildiz O T,Alpaydin E.Omnivariate decision trees[J].IEEE Transactions on Neural Networks,2001,12(6):1539-1546.
9Swere E,Mulvaney D J.Robot navigation using decision trees[R].Loughborougk,UK:Electronic Systems and Control Division Research,2003.
10Brezillon P,Pasquier L,Pomerol J.Context and decision graphs in incident management on a subway line[C].Trento,Italy:Proceedings of the 2nd International and Interdisciplinary Conference on Modeling and Using Context,1999.