Geoffrey I. Webb

Nayyar A. Zaidi, Geoffrey I. Webb: Fast and Effective Single Pass Bayesian Learning. PAKDD (1) 2013: 149-160

Geoffrey I. Webb, Janice R. Boughton, Fei Zheng, Kai Ming Ting, Houssam Salem: Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification. Machine Learning 86(2): 233-272 (2012)

Fei Zheng, Geoffrey I. Webb, Pramuditha Suraweera, Liguang Zhu: Subsumption resolution: an efficient and effective technique for semi-naive Bayesian learning. Machine Learning 87(1): 93-125 (2012)

Geoffrey I. Webb: Discovering Associations in High-Dimensional Data. ADC 2012: 7

Ana M. Martínez, Geoffrey I. Webb, M. Julia Flores, José A. Gámez: Non-Disjoint Discretization for Aggregating One-Dependence Estimator Classifiers. HAIS (2) 2012: 151-162

Houssam Salem, Pramuditha Suraweera, Geoffrey I. Webb, Janice R. Boughton: Techniques for Efficient Learning without Search. PAKDD (1) 2012: 50-61

Mohammed Javeed Zaki, Arno Siebes, Jeffrey Xu Yu, Bart Goethals, Geoffrey I. Webb, Xindong Wu (Eds.): 12th IEEE International Conference on Data Mining, ICDM 2012, Brussels, Belgium, December 10-13, 2012. IEEE Computer Society 2012, isbn 978-1-4673-4649-8

Jilles Vreeken, Charles Ling, Mohammed Javeed Zaki, Arno Siebes, Jeffrey Xu Yu, Bart Goethals, Geoffrey I. Webb, Xindong Wu (Eds.): 12th IEEE International Conference on Data Mining Workshops, ICDM Workshops, Brussels, Belgium, December 10, 2012. IEEE Computer Society 2012, isbn 978-1-4673-5164-5

Jiangning Song, Hao Tan, Sarah E. Boyd, Hongbin Shen, Khalid Mahmood, Geoffrey I. Webb, Tatsuya Akutsu, James C. Whisstock, Robert N. Pike: Bioinformatic Approaches for Predicting substrates of Proteases. J. Bioinformatics and Computational Biology 9(1): 149-178 (2011)

Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb: Feature-subspace aggregating: ensembles for stable and unstable learners. Machine Learning 82(3): 375-397 (2011)

Geoffrey I. Webb: Filtered-top-k association discovery. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 1(3): 183-192 (2011)

Claude Sammut, Geoffrey I. Webb (Eds.): Encyclopedia of Machine Learning. Springer 2010, isbn 978-0-387-30768-8

Jiangning Song, Hao Tan, Hongbin Shen, Khalid Mahmood, Sarah E. Boyd, Geoffrey I. Webb, Tatsuya Akutsu, James C. Whisstock: Cascleave: towards more accurate prediction of caspase substrate cleavage sites. Bioinformatics 26(6): 752-760 (2010)

Khalid Mahmood, Arun Siddharth Konagurthu, Jiangning Song, Ashley M. Buckle, Geoffrey I. Webb, James C. Whisstock: EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes. Bioinformatics 26(17): 2076-2084 (2010)

Geoffrey I. Webb: Self-sufficient itemsets: An approach to screening potentially interesting associations between items. TKDD 4(1) (2010)

Ying Yang, Geoffrey I. Webb, Xindong Wu: Discretization Methods. Data Mining and Knowledge Discovery Handbook 2010: 101-116

Geoffrey I. Webb: Algorithm Evaluation. Encyclopedia of Machine Learning 2010: 35-36

Fei Zheng, Geoffrey I. Webb: Averaged One-Dependence Estimators. Encyclopedia of Machine Learning 2010: 63-64

Geoffrey I. Webb: Bayes Rule. Encyclopedia of Machine Learning 2010: 74-75

Geoffrey I. Webb: Data Preparation. Encyclopedia of Machine Learning 2010: 259-260

Bin Liu, Geoffrey I. Webb: Generative and Discriminative Learning. Encyclopedia of Machine Learning 2010: 454-455

Geoffrey I. Webb: Lazy Learning. Encyclopedia of Machine Learning 2010: 571-572

Geoffrey I. Webb: Model Evaluation. Encyclopedia of Machine Learning 2010: 683

Geoffrey I. Webb: MultiBoosting. Encyclopedia of Machine Learning 2010: 699-701

Geoffrey I. Webb: Naïve Bayes. Encyclopedia of Machine Learning 2010: 713-714

Geoffrey I. Webb: Occam's Razor. Encyclopedia of Machine Learning 2010: 735

Geoffrey I. Webb: Overfitting. Encyclopedia of Machine Learning 2010: 744

Geoffrey I. Webb: Posterior Probability. Encyclopedia of Machine Learning 2010: 780

Geoffrey I. Webb: Prior Probability. Encyclopedia of Machine Learning 2010: 782

Fei Zheng, Geoffrey I. Webb: Semi-Naive Bayesian Learning. Encyclopedia of Machine Learning 2010: 889-892

Petra Kralj Novak, Nada Lavrac, Geoffrey I. Webb: Supervised Descriptive Rule Induction. Encyclopedia of Machine Learning 2010: 938-941

Fei Zheng, Geoffrey I. Webb: Tree Augmented Naive Bayes. Encyclopedia of Machine Learning 2010: 990-991

Geoffrey I. Webb, Bing Liu, Chengqi Zhang, Dimitrios Gunopulos, Xindong Wu (Eds.): ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010. IEEE Computer Society 2010

Wei Fan, Wynne Hsu, Geoffrey I. Webb, Bing Liu, Chengqi Zhang, Dimitrios Gunopulos, Xindong Wu (Eds.): ICDMW 2010, The 10th IEEE International Conference on Data Mining Workshops, Sydney, Australia, 14 December 2010. IEEE Computer Society 2010

Petra Kralj Novak, Nada Lavrac, Geoffrey I. Webb: Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining. Journal of Machine Learning Research 10: 377-403 (2009)

Ying Yang, Geoffrey I. Webb: Discretization for naive-Bayes learning: managing discretization bias and variance. Machine Learning 74(1): 39-74 (2009)

Bei Hui, Ying Yang, Geoffrey I. Webb: Anytime classification for a pool of instances. Machine Learning 77(1): 61-102 (2009)

Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb: FaSS: Ensembles for Stable Learners. MCS 2009: 364-374

Bin Liu, Ying Yang, Geoffrey I. Webb, Janice R. Boughton: A Comparative Study of Bandwidth Choice in Kernel Density Estimation for Naive Bayesian Classification. PAKDD 2009: 302-313

Geoffrey I. Webb: Discovering significant patterns. Machine Learning 71(1): 131 (2008)

Geoffrey I. Webb: Layered critical values: a powerful direct-adjustment approach to discovering significant patterns. Machine Learning 71(2-3): 307-323 (2008)

Geoffrey I. Webb: Multi-Strategy Ensemble Learning, Ensembles of Bayesian Classifiers, and the Problem of False Discoveries. AusDM 2008: 15

Geoffrey I. Webb: Editorial. Data Min. Knowl. Discov. 15(1): 1-2 (2007)

Geoffrey I. Webb: Discovering Significant Patterns. Machine Learning 68(1): 1-33 (2007)

Ying Yang, Geoffrey I. Webb, Kevin B. Korb, Kai Ming Ting: Classifying under computational resource constraints: anytime classification using probabilistic estimators. Machine Learning 69(1): 35-53 (2007)

Ying Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting: To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators. IEEE Trans. Knowl. Data Eng. 19(12): 1652-1665 (2007)

Fei Zheng, Geoffrey I. Webb: Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators. ECML 2007: 490-501

Geoffrey I. Webb: Finding the Real Patterns. PAKDD 2007: 6

Jingli Lu, Ying Yang, Geoffrey I. Webb: Incremental Discretization for Naïve-Bayes Classifier. ADMA 2006: 223-238

Geoffrey I. Webb: Anytime learning and classification for online applications. AMT 2006: 7-12

Geoffrey I. Webb, Damien Brain: Generality Is Predictive of Prediction Accuracy. Selected Papers from AusDM 2006: 1-13

Shiying Huang, Geoffrey I. Webb: Efficiently Identifying Exploratory Rules' Significance. Selected Papers from AusDM 2006: 64-77

Ying Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting: To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles. ECML 2006: 533-544

Fei Zheng, Geoffrey I. Webb: Efficient lazy elimination for averaged one-dependence estimators. ICML 2006: 1113-1120

Geoffrey I. Webb: Discovering significant rules. KDD 2006: 434-443

Qiang Yang, Geoffrey I. Webb (Eds.): PRICAI 2006: Trends in Artificial Intelligence, 9th Pacific Rim International Conference on Artificial Intelligence, Guilin, China, August 7-11, 2006, Proceedings. Lecture Notes in Computer Science 4099, Springer 2006, isbn 3-540-36667-9

Geoffrey I. Webb, Songmao Zhang: K-Optimal Rule Discovery. Data Min. Knowl. Discov. 10(1): 39-79 (2005)

Geoffrey I. Webb, Janice R. Boughton, Zhihai Wang: Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning 58(1): 5-24 (2005)

Geoffrey I. Webb, Kai Ming Ting: On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions. Machine Learning 58(1): 25-32 (2005)

Ying Yang, Geoffrey I. Webb, Xindong Wu: Discretization Methods. The Data Mining and Knowledge Discovery Handbook 2005: 113-130

Geoffrey I. Webb: K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining. Australian Conference on Artificial Intelligence 2005: 1-2

Ying Yang, Kevin B. Korb, Kai Ming Ting, Geoffrey I. Webb: Ensemble Selection for SuperParent-One-Dependence Estimators. Australian Conference on Artificial Intelligence 2005: 102-112

Shiying Huang, Geoffrey I. Webb: Pruning Derivative Partial Rules During Impact Rule Discovery. PAKDD 2005: 71-80

Shiying Huang, Geoffrey I. Webb: Discarding Insignificant Rules during Impact Rule Discovery in Large, Dense Databases. SDM 2005

Honghua Dai, Geoffrey I. Webb: Guest Editors' Introduction. International Journal of Software Engineering and Knowledge Engineering 14(4): 365-368 (2004)

Geoffrey I. Webb, Zijian Zheng: Multistrategy Ensemble Learning: Reducing Error by Combining Ensemble Learning Techniques. IEEE Trans. Knowl. Data Eng. 16(8): 980-991 (2004)

Dhananjay R. Thiruvady, Geoffrey I. Webb: Mining Negative Rules Using GRD. PAKDD 2004: 161-165

Zhihai Wang, Geoffrey I. Webb, Fei Zheng: Selective Augmented Bayesian Network Classifiers Based on Rough Set Theory. PAKDD 2004: 319-328

Geoffrey I. Webb, Xinghuo Yu (Eds.): AI 2004: Advances in Artificial Intelligence, 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004, Proceedings. Lecture Notes in Computer Science 3339, Springer 2004, isbn 3-540-24059-4

Chengqi Zhang, Shichao Zhang, Geoffrey I. Webb: Identifying Approximate Itemsets of Interest in Large Databases. Appl. Intell. 18(1): 91-104 (2003)

Ying Yang, Geoffrey I. Webb: On Why Discretization Works for Naive-Bayes Classifiers. Australian Conference on Artificial Intelligence 2003: 440-452

Zhihai Wang, Geoffrey I. Webb, Fei Zheng: Adjusting Dependence Relations for Semi-Lazy TAN Classifiers. Australian Conference on Artificial Intelligence 2003: 453-465

Shane M. Butler, Geoffrey I. Webb, Rob A. Lewis: A Case Study in Feature Invention for Breast Cancer Diagnosis Using X-Ray Scatter Images. Australian Conference on Artificial Intelligence 2003: 677-685

Geoffrey I. Webb, Shane M. Butler, Douglas A. Newlands: On detecting differences between groups. KDD 2003: 256-265

Hongbo Shi, Zhihai Wang, Geoffrey I. Webb, Houkuan Huang: A New Restricted Bayesian Network Classifier. PAKDD 2003: 265-270

Ying Yang, Geoffrey I. Webb: Weighted Proportional k-Interval Discretization for Naive-Bayes Classifiers. PAKDD 2003: 501-512

Yakov Frayman, Bernard F. Rolfe, Geoffrey I. Webb: Solving Regression Problems Using Competitive Ensemble Models. Australian Joint Conference on Artificial Intelligence 2002: 511-522

Zhihai Wang, Geoffrey I. Webb: Comparison of Lazy Bayesian Rule and Tree-Augmented Bayesian Learning. ICDM 2002: 490-497

James E. Pearce, Geoffrey I. Webb, Robin N. Shaw, Brian Garner: Experimentation and Self Learning in Continuous Database Marketing. ICDM 2002: 775-778

Ying Yang, Geoffrey I. Webb: Non-Disjoint Discretization for Naive-Bayes Classifiers. ICML 2002: 666-673

Damien Brain, Geoffrey I. Webb: The Need for Low Bias Algorithms in Classification Learning from Large Data Sets. PKDD 2002: 62-73

Geoffrey I. Webb, Michael J. Pazzani, Daniel Billsus: Machine Learning for User Modeling. User Model. User-Adapt. Interact. 11(1-2): 19-29 (2001)

Geoffrey I. Webb: Candidate Elimination Criteria for Lazy Bayesian Rules. Australian Joint Conference on Artificial Intelligence 2001: 545-556

Songmao Zhang, Geoffrey I. Webb: Further Pruning for Efficient Association Rule Discovery. Australian Joint Conference on Artificial Intelligence 2001: 605-618

Ying Yang, Geoffrey I. Webb: Proportional k-Interval Discretization for Naive-Bayes Classifiers. ECML 2001: 564-575

Geoffrey I. Webb: Discovering associations with numeric variables. KDD 2001: 383-388

Geoffrey I. Webb: MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning 40(2): 159-196 (2000)

Zijian Zheng, Geoffrey I. Webb: Lazy Learning of Bayesian Rules. Machine Learning 41(1): 53-84 (2000)

Geoffrey I. Webb: Efficient search for association rules. KDD 2000: 99-107

Geoffrey I. Webb, Jason Wells, Zijian Zheng: An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition. Machine Learning 35(1): 5-23 (1999)

Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting: Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees. ICML 1999: 493-502

Geoffrey I. Webb: Decision Tree Grafting From the All Tests But One Partition. IJCAI 1999: 702-707

Zijian Zheng, Geoffrey I. Webb: Stochastic Attribute Selection Committees with Aultiple Boosting: Learning More Accurate and More Stable Classifer Committees. PAKDD 1999: 123-132

Douglas A. Newlands, Geoffrey I. Webb: Convex Hulls in Concept Induction. PAKDD 1999: 306-316

Geoffrey I. Webb: Preface to UMUAI Special Issue on Machine Learning for User Modeling. User Model. User-Adapt. Interact. 8(1-2): 1-3 (1998)

Bark Cheung Chiu, Geoffrey I. Webb: Using Decision Trees for Agent Modeling: Improving Prediction Performance. User Model. User-Adapt. Interact. 8(1-2): 131-152 (1998)

Geoffrey I. Webb: The Problem of Missing Values in Decision Tree Grafting. Australian Joint Conference on Artificial Intelligence 1998: 273-283

Geoffrey I. Webb, Michael J. Pazzani: Adjusted Probability Naive Bayesian Induction. Australian Joint Conference on Artificial Intelligence 1998: 285-295

Zijian Zheng, Geoffrey I. Webb: Stochastic Attribute Selection Committees. Australian Joint Conference on Artificial Intelligence 1998: 321-332

Murlikrishna Viswanathan, Geoffrey I. Webb: Classification Learning Using All Rules. ECML 1998: 149-159

Geoffrey I. Webb, Mark Kuzmycz: Evaluation of Data Aging: A Technique for Discounting Old Data During Student Modeling. Intelligent Tutoring Systems 1998: 384-393

Bark Cheung Chiu, Geoffrey I. Webb, Zijian Zheng: Using Decision Trees for Agent Modelling: A Study on Resolving Confliction Predictions. Australian Joint Conference on Artificial Intelligence 1997: 349-358

Geoffrey I. Webb: Decision Tree Grafting. IJCAI (2) 1997: 846-851

Geoffrey I. Webb: Further Experimental Evidence against the Utility of Occam's Razor. J. Artif. Intell. Res. (JAIR) 4: 397-417 (1996)

Geoffrey I. Webb: Integrating machine learning with knowledge acquisition through direct interaction with domain experts. Knowl.-Based Syst. 9(4): 253-266 (1996)

Geoffrey I. Webb: Cost-Sensitive Specialization. PRICAI 1996: 23-34

Geoffrey I. Webb: Further Experimental Evidence against the Utility of Occam's Razor. CoRR cs.AI/9605101 (1996)

Geoffrey I. Webb: OPUS: An Efficient Admissible Algorithm for Unordered Search. J. Artif. Intell. Res. (JAIR) 3: 431-465 (1995)

Geoffrey I. Webb, Mark Kuzmycz: Feature Based Modelling: A Methodology for Producing Coherent, Consistent, Dynamically Changing Models of Agents' Competencies. User Model. User-Adapt. Interact. 5(2): 117-150 (1995)

Philip A. Smith, Geoffrey I. Webb: Transparency Debugging with Explanations for Novice Programmers. AADEBUG 1995: 105-118

Douglas A. Newlands, Geoffrey I. Webb: Polygonal Inductive Generalisation System. IEA/AIE 1995: 587-592

Geoffrey I. Webb, John W. M. Agar: Inducing diagnostic rules for glomerular disease with the DLG machine learning algorithm. Artificial Intelligence in Medicine 4(6): 419-430 (1992)

Mark Kuzmycz, Geoffrey I. Webb: Evaluation of Feature Based Modelling in Subtraction. Intelligent Tutoring Systems 1992: 269-276

Louis Sanzogn, Francis Suraweera, Geoffrey I. Webb: Improving the efficiency of rule-based expert systems by rule activation. J. Exp. Theor. Artif. Intell. 2(4): 369-380 (1990)

Geoffrey I. Webb: A Knowledge-Based Approach to Computer-Aided Learning. International Journal of Man-Machine Studies 29(3): 257-285 (1988)

Geoffrey I. Webb: Techniques for Efficient Empirical Induction. Australian Joint Conference on Artificial Intelligence 1988: 225-239