| 2009 |
|---|
| 76 | EE | 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 |
| 2008 |
|---|
| 75 | | Geoffrey I. Webb:
Multi-Strategy Ensemble Learning, Ensembles of Bayesian Classifiers, and the Problem of False Discoveries.
AusDM 2008: 15 |
| 74 | EE | Geoffrey I. Webb:
Discovering significant patterns.
Machine Learning 71(1): 131 (2008) |
| 73 | EE | Geoffrey I. Webb:
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns.
Machine Learning 71(2-3): 307-323 (2008) |
| 2007 |
|---|
| 72 | EE | Fei Zheng,
Geoffrey I. Webb:
Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators.
ECML 2007: 490-501 |
| 71 | EE | Geoffrey I. Webb:
Finding the Real Patterns.
PAKDD 2007: 6 |
| 70 | EE | Geoffrey I. Webb:
Editorial.
Data Min. Knowl. Discov. 15(1): 1-2 (2007) |
| 69 | EE | 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) |
| 68 | EE | Geoffrey I. Webb:
Discovering Significant Patterns.
Machine Learning 68(1): 1-33 (2007) |
| 67 | EE | 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) |
| 2006 |
|---|
| 66 | | Qiang Yang,
Geoffrey I. Webb:
PRICAI 2006: Trends in Artificial Intelligence, 9th Pacific Rim International Conference on Artificial Intelligence, Guilin, China, August 7-11, 2006, Proceedings
Springer 2006 |
| 65 | EE | Jingli Lu,
Ying Yang,
Geoffrey I. Webb:
Incremental Discretization for Naïve-Bayes Classifier.
ADMA 2006: 223-238 |
| 64 | | Geoffrey I. Webb:
Anytime learning and classification for online applications.
AMT 2006: 7-12 |
| 63 | EE | 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 |
| 62 | EE | Fei Zheng,
Geoffrey I. Webb:
Efficient lazy elimination for averaged one-dependence estimators.
ICML 2006: 1113-1120 |
| 61 | EE | Geoffrey I. Webb:
Discovering significant rules.
KDD 2006: 434-443 |
| 60 | EE | Geoffrey I. Webb,
Damien Brain:
Generality Is Predictive of Prediction Accuracy.
Selected Papers from AusDM 2006: 1-13 |
| 59 | EE | Shiying Huang,
Geoffrey I. Webb:
Efficiently Identifying Exploratory Rules' Significance.
Selected Papers from AusDM 2006: 64-77 |
| 2005 |
|---|
| 58 | EE | Geoffrey I. Webb:
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining.
Australian Conference on Artificial Intelligence 2005: 1-2 |
| 57 | EE | 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 |
| 56 | EE | Shiying Huang,
Geoffrey I. Webb:
Pruning Derivative Partial Rules During Impact Rule Discovery.
PAKDD 2005: 71-80 |
| 55 | | Shiying Huang,
Geoffrey I. Webb:
Discarding Insignificant Rules during Impact Rule Discovery in Large, Dense Databases.
SDM 2005 |
| 54 | | Ying Yang,
Geoffrey I. Webb,
Xindong Wu:
Discretization Methods.
The Data Mining and Knowledge Discovery Handbook 2005: 113-130 |
| 53 | EE | Geoffrey I. Webb,
Songmao Zhang:
K-Optimal Rule Discovery.
Data Min. Knowl. Discov. 10(1): 39-79 (2005) |
| 52 | EE | 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) |
| 51 | EE | Geoffrey I. Webb,
Janice R. Boughton,
Zhihai Wang:
Not So Naive Bayes: Aggregating One-Dependence Estimators.
Machine Learning 58(1): 5-24 (2005) |
| 2004 |
|---|
| 50 | | Geoffrey I. Webb,
Xinghuo Yu:
AI 2004: Advances in Artificial Intelligence, 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004, Proceedings
Springer 2004 |
| 49 | EE | Dhananjay R. Thiruvady,
Geoffrey I. Webb:
Mining Negative Rules Using GRD.
PAKDD 2004: 161-165 |
| 48 | EE | Zhihai Wang,
Geoffrey I. Webb,
Fei Zheng:
Selective Augmented Bayesian Network Classifiers Based on Rough Set Theory.
PAKDD 2004: 319-328 |
| 47 | EE | 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) |
| 46 | EE | Honghua Dai,
Geoffrey I. Webb:
Guest Editors' Introduction.
International Journal of Software Engineering and Knowledge Engineering 14(4): 365-368 (2004) |
| 2003 |
|---|
| 45 | EE | Ying Yang,
Geoffrey I. Webb:
On Why Discretization Works for Naive-Bayes Classifiers.
Australian Conference on Artificial Intelligence 2003: 440-452 |
| 44 | EE | Zhihai Wang,
Geoffrey I. Webb,
Fei Zheng:
Adjusting Dependence Relations for Semi-Lazy TAN Classifiers.
Australian Conference on Artificial Intelligence 2003: 453-465 |
| 43 | EE | 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 |
| 42 | EE | Geoffrey I. Webb,
Shane M. Butler,
Douglas A. Newlands:
On detecting differences between groups.
KDD 2003: 256-265 |
| 41 | EE | Hongbo Shi,
Zhihai Wang,
Geoffrey I. Webb,
Houkuan Huang:
A New Restricted Bayesian Network Classifier.
PAKDD 2003: 265-270 |
| 40 | EE | Ying Yang,
Geoffrey I. Webb:
Weighted Proportional k-Interval Discretization for Naive-Bayes Classifiers.
PAKDD 2003: 501-512 |
| 39 | | Chengqi Zhang,
Shichao Zhang,
Geoffrey I. Webb:
Identifying Approximate Itemsets of Interest in Large Databases.
Appl. Intell. 18(1): 91-104 (2003) |
| 2002 |
|---|
| 38 | EE | Yakov Frayman,
Bernard F. Rolfe,
Geoffrey I. Webb:
Solving Regression Problems Using Competitive Ensemble Models.
Australian Joint Conference on Artificial Intelligence 2002: 511-522 |
| 37 | EE | Zhihai Wang,
Geoffrey I. Webb:
Comparison of Lazy Bayesian Rule and Tree-Augmented Bayesian Learning.
ICDM 2002: 490-497 |
| 36 | EE | James E. Pearce,
Geoffrey I. Webb,
Robin N. Shaw,
Brian Garner:
Experimentation and Self Learning in Continuous Database Marketing.
ICDM 2002: 775-778 |
| 35 | | Ying Yang,
Geoffrey I. Webb:
Non-Disjoint Discretization for Naive-Bayes Classifiers.
ICML 2002: 666-673 |
| 34 | EE | Damien Brain,
Geoffrey I. Webb:
The Need for Low Bias Algorithms in Classification Learning from Large Data Sets.
PKDD 2002: 62-73 |
| 2001 |
|---|
| 33 | EE | Geoffrey I. Webb:
Candidate Elimination Criteria for Lazy Bayesian Rules.
Australian Joint Conference on Artificial Intelligence 2001: 545-556 |
| 32 | EE | Songmao Zhang,
Geoffrey I. Webb:
Further Pruning for Efficient Association Rule Discovery.
Australian Joint Conference on Artificial Intelligence 2001: 605-618 |
| 31 | EE | Ying Yang,
Geoffrey I. Webb:
Proportional k-Interval Discretization for Naive-Bayes Classifiers.
ECML 2001: 564-575 |
| 30 | EE | Geoffrey I. Webb:
Discovering associations with numeric variables.
KDD 2001: 383-388 |
| 29 | EE | Geoffrey I. Webb,
Michael J. Pazzani,
Daniel Billsus:
Machine Learning for User Modeling.
User Model. User-Adapt. Interact. 11(1-2): 19-29 (2001) |
| 2000 |
|---|
| 28 | EE | Geoffrey I. Webb:
Efficient search for association rules.
KDD 2000: 99-107 |
| 27 | | Geoffrey I. Webb:
MultiBoosting: A Technique for Combining Boosting and Wagging.
Machine Learning 40(2): 159-196 (2000) |
| 26 | | Zijian Zheng,
Geoffrey I. Webb:
Lazy Learning of Bayesian Rules.
Machine Learning 41(1): 53-84 (2000) |
| 1999 |
|---|
| 25 | | 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 |
| 24 | | Geoffrey I. Webb:
Decision Tree Grafting From the All Tests But One Partition.
IJCAI 1999: 702-707 |
| 23 | EE | Zijian Zheng,
Geoffrey I. Webb:
Stochastic Attribute Selection Committees with Aultiple Boosting: Learning More Accurate and More Stable Classifer Committees.
PAKDD 1999: 123-132 |
| 22 | EE | Douglas A. Newlands,
Geoffrey I. Webb:
Convex Hulls in Concept Induction.
PAKDD 1999: 306-316 |
| 21 | | Geoffrey I. Webb,
Jason Wells,
Zijian Zheng:
An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition.
Machine Learning 35(1): 5-23 (1999) |
| 1998 |
|---|
| 20 | | Geoffrey I. Webb:
The Problem of Missing Values in Decision Tree Grafting.
Australian Joint Conference on Artificial Intelligence 1998: 273-283 |
| 19 | | Geoffrey I. Webb,
Michael J. Pazzani:
Adjusted Probability Naive Bayesian Induction.
Australian Joint Conference on Artificial Intelligence 1998: 285-295 |
| 18 | | Zijian Zheng,
Geoffrey I. Webb:
Stochastic Attribute Selection Committees.
Australian Joint Conference on Artificial Intelligence 1998: 321-332 |
| 17 | | Murlikrishna Viswanathan,
Geoffrey I. Webb:
Classification Learning Using All Rules.
ECML 1998: 149-159 |
| 16 | EE | Geoffrey I. Webb,
Mark Kuzmycz:
Evaluation of Data Aging: A Technique for Discounting Old Data During Student Modeling.
Intelligent Tutoring Systems 1998: 384-393 |
| 15 | EE | 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) |
| 14 | EE | 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) |
| 1997 |
|---|
| 13 | | 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 |
| 12 | | Geoffrey I. Webb:
Decision Tree Grafting.
IJCAI (2) 1997: 846-851 |
| 1996 |
|---|
| 11 | | Geoffrey I. Webb:
Cost-Sensitive Specialization.
PRICAI 1996: 23-34 |
| 10 | EE | Geoffrey I. Webb:
Further Experimental Evidence against the Utility of Occam's Razor
CoRR cs.AI/9605101: (1996) |
| 9 | | Geoffrey I. Webb:
Further Experimental Evidence against the Utility of Occam's Razor.
J. Artif. Intell. Res. (JAIR) 4: 397-417 (1996) |
| 8 | EE | Geoffrey I. Webb:
Integrating machine learning with knowledge acquisition through direct interaction with domain experts.
Knowl.-Based Syst. 9(4): 253-266 (1996) |
| 1995 |
|---|
| 7 | | Philip A. Smith,
Geoffrey I. Webb:
Transparency Debugging with Explanations for Novice Programmers.
AADEBUG 1995: 105-118 |
| 6 | EE | Douglas A. Newlands,
Geoffrey I. Webb:
Polygonal Inductive Generalisation System.
IEA/AIE 1995: 587-592 |
| 5 | | Geoffrey I. Webb:
OPUS: An Efficient Admissible Algorithm for Unordered Search.
J. Artif. Intell. Res. (JAIR) 3: 431-465 (1995) |
| 4 | | 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) |
| 1992 |
|---|
| 3 | | Mark Kuzmycz,
Geoffrey I. Webb:
Evaluation of Feature Based Modelling in Subtraction.
Intelligent Tutoring Systems 1992: 269-276 |
| 1988 |
|---|
| 2 | | Geoffrey I. Webb:
Techniques for Efficient Empirical Induction.
Australian Joint Conference on Artificial Intelligence 1988: 225-239 |
| 1 | | Geoffrey I. Webb:
A Knowledge-Based Approach to Computer-Aided Learning.
International Journal of Man-Machine Studies 29(3): 257-285 (1988) |
