| Discretization for naive-Bayes learning: managing discretization bias and variance Y Yang, GI Webb Machine learning 74, 39-74, 2009 | 326 | 2009 |
| A comparative study of discretization methods for naive-bayes classifiers Y Yang, GI Webb Proceedings of PKAW 2002, 2002 | 264 | 2002 |
| Discretization methods Y Yang, GI Webb, X Wu Data mining and knowledge discovery handbook, 101-116, 2010 | 166 | 2010 |
| Combining proactive and reactive predictions for data streams Y Yang, X Wu, X Zhu Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 164 | 2005 |
| Proportional k-interval discretization for naive-Bayes classifiers Y Yang, GI Webb Machine Learning: ECML 2001: 12th European Conference on Machine Learning …, 2001 | 164 | 2001 |
| Mining in anticipation for concept change: Proactive-reactive prediction in data streams Y Yang, X Wu, X Zhu Data mining and knowledge discovery 13, 261-289, 2006 | 137 | 2006 |
| Adapted one-versus-all decision trees for data stream classification S Hashemi, Y Yang, Z Mirzamomen, M Kangavari IEEE Transactions on Knowledge and Data Engineering 21 (5), 624-637, 2008 | 131 | 2008 |
| On why discretization works for naive-bayes classifiers Y Yang, GI Webb Australasian Joint Conference on Artificial Intelligence, 440-452, 2003 | 129 | 2003 |
| Dynamic classifier selection for effective mining from noisy data streams X Zhu, X Wu, Y Yang Fourth IEEE International Conference on Data Mining (ICDM'04), 305-312, 2004 | 122 | 2004 |
| Error detection and impact-sensitive instance ranking in noisy datasets X Zhu, X Wu, Y Yang Proceedings of the national conference on artificial intelligence, 378-384, 2004 | 87 | 2004 |
| Flexible decision tree for data stream classification in the presence of concept change, noise and missing values S Hashemi, Y Yang Data Mining and Knowledge Discovery 19, 95-131, 2009 | 83 | 2009 |
| Weighted proportional k-interval discretization for naive-bayes classifiers Y Yang, GI Webb Pacific-Asia Conference on Knowledge Discovery and Data Mining, 501-512, 2003 | 63 | 2003 |
| Ensemble selection for superparent-one-dependence estimators Y Yang, K Korb, KM Ting, GI Webb AI 2005: Advances in Artificial Intelligence: 18th Australian Joint …, 2005 | 62 | 2005 |
| To select or to weigh: A comparative study of linear combination schemes for superparent-one-dependence estimators Y Yang, GI Webb, J Cerquides, KB Korb, J Boughton, KM Ting IEEE Transactions on Knowledge and Data Engineering 19 (12), 1652-1665, 2007 | 60 | 2007 |
| Effective classification of noisy data streams with attribute-oriented dynamic classifier selection X Zhu, X Wu, Y Yang Knowledge and Information Systems 9, 339-363, 2006 | 50 | 2006 |
| A lazy bagging approach to classification X Zhu, Y Yang Pattern Recognition 41 (10), 2980-2992, 2008 | 48 | 2008 |
| Classifying under computational resource constraints: anytime classification using probabilistic estimators Y Yang, G Webb, K Korb, KM Ting Machine Learning 69, 35-53, 2007 | 48 | 2007 |
| Dealing with predictive-but-unpredictable attributes in noisy data sources Y Yang, X Wu, X Zhu Knowledge Discovery in Databases: PKDD 2004: 8th European Conference on …, 2004 | 47 | 2004 |
| Discretization for naive-bayes learning Y Yang Monash University, 2003 | 47 | 2003 |
| Detecting intrusion transactions in databases using data item dependencies and anomaly analysis S Hashemi, Y Yang, D Zabihzadeh, M Kangavari Expert Systems 25 (5), 460-473, 2008 | 39 | 2008 |
