11.Hui, B., Y. Yang, and G.I. Webb (2009). Anytime Classification for a Pool of Instances. Machine Learning 77(1). Netherlands: Springer, pages 61-102. [Abstract] [Pre-publication PDF][Link to paper via Springerlink]
10.Yang, Y. and G.I. Webb (2009). Discretization for Naive-Bayes Learning: Managing Discretization Bias and Variance. Machine Learning 74(1). Netherlands: Springer, pages 39-74. [Abstract] [Pre-Publication PDF][Link to paper via Springerlink]
9.Yang, Y., G.I. Webb, K. Korb, and K-M. Ting (2007). Classifying under Computational Resource Constraints: Anytime Classification Using Probabilistic Estimators. Machine Learning 69(1). Netherlands: Springer, pages 35-53. [Abstract] [Pre-publication PDF][Link to paper via Springerlink]
8.Yang, Y., G.I. Webb, J. Cerquides, K. Korb, J. Boughton, and K-M. Ting (2007). To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators. IEEE Transactions on Knowledge and Data Engineering (TKDE) 19(12). Los Alamitos, CA: IEEE Computer Society, pages 1652-1665. [Abstract] [Pre-publication PDF][ Link to paper via IEEE]
7.Zheng, F. and G.I. Webb (2007). Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators. In Lecture Notes in Artificial Intelligence 4710: Proceedings of the 18th European Conference on Machine Learning (ECML'07) Warsaw, Poland. Berlin/Heidelberg: Springer-Verlag, pages 490-501. [Abstract] [Pre-publication PDF]
6.Zheng, F. and G.I. Webb (2006). Efficient Lazy Elimination for Averaged One-Dependence Estimators. In W. Cohen and A. Moore (Eds.), ACM International Conference Proceeding Series, Vol. 148: The Proceedings of the Twenty-third International Conference on Machine Learning (ICML'06) Pittsburgh, Pennsylvania. New York, NY: ACM Press, pages 1113 - 1120. [Abstract] [Pre-publication PDF][Link to paper via ACM Portal]
5.Yang, Y., G.I. Webb, J. Cerquides, K. Korb, J. Boughton, and K-M. Ting (2006). To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles. In J. Furkranz, T. Scheffer and M. Spiliopoulou (Eds.), Lecture Notes in Computer Science 4212: Proceedings of the 17th European Conference on Machine Learning (ECML'06) Berlin, Germany. Berlin/Heidelberg: Springer-Verlag, pages 533-544. [Abstract] [Pre-publication PDF][Link to paper via Springerlink]
4.Webb, G. I., J. Boughton, and Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning 58(1). Netherlands: Springer, pages 5-24. [Abstract] [Pre-publication PDF][Link to paper via Springerlink]
3.Yang, Y., K. Korb, K-M. Ting, and G.I. Webb (2005). Ensemble Selection for SuperParent-One-Dependence Estimators. In S. Zhang and R. Jarvis (Eds.), Lecture Notes in Computer Science 3809: Advances in Artificial Intelligence, Proceedings of the 18th Australian Joint Conference on Artificial Intelligence (AI 2005) Sydney, Australia. Berlin/Heidelberg: Springer, pages 102-111. [Abstract] [Pre-publication PDF][Link to paper via Springerlink]
2.Zheng, F. and G.I. Webb (2005). A Comparative Study of Semi-naive Bayes Methods in Classification Learning. In S.J. Simoff, G.J. Williams, J. Galloway and I. Kolyshkina (Eds.), Proceedings of the Fourth Australasian Data Mining Conference (AusDM05) Sydney, Australia. Sydney: University of Technology, pages 141-156. [Abstract] [Pre-publication PDF]
1.Webb, G. I., J. Boughton, and Z. Wang (2002). Averaged One-Dependence Estimators: Preliminary Results. In S.J Simoff, G.J Williams and M. Hegland (Eds.), Proceedings of the First Australasian Data Mining Workshop (AusDM02) Canberra, Australia. Sydney: University of Technology, pages 65-73. [Abstract] [PDF]