| 2009 | ||
|---|---|---|
| 50 | Eibe Frank, Remco R. Bouckaert: Conditional Density Estimation with Class Probability Estimators. ACML 2009: 65-81 | |
| 49 | Martin Gutlein, Eibe Frank, Mark Hall, Andreas Karwath: Large-scale attribute selection using wrappers. CIDM 2009: 332-339 | |
| 48 | Jesse Read, Bernhard Pfahringer, Geoffrey Holmes, Eibe Frank: Classifier Chains for Multi-label Classification. ECML/PKDD (2) 2009: 254-269 | |
| 47 | Geoffrey Holmes, Dale Fletcher, Peter Reutemann, Eibe Frank: Analysing chromatographic data using data mining to monitor petroleum content in water. ITEE 2009: 278-290 | |
| 46 | Anna Huang, David N. Milne, Eibe Frank, Ian H. Witten: Clustering Documents Using a Wikipedia-Based Concept Representation. PAKDD 2009: 628-636 | |
| 45 | Arie Ben-David, Eibe Frank: Accuracy of machine learning models versus "hand crafted" expert systems - A credit scoring case study. Expert Syst. Appl. 36(3): 5264-5271 (2009) | |
| 2008 | ||
| 44 | James R. Foulds, Eibe Frank: Revisiting Multiple-Instance Learning Via Embedded Instance Selection. Australasian Conference on Artificial Intelligence 2008: 300-310 | |
| 43 | Kathryn Hempstalk, Eibe Frank: Discriminating Against New Classes: One-class versus Multi-class Classification. Australasian Conference on Artificial Intelligence 2008: 325-336 | |
| 42 | Eibe Frank, Mark Hall: Additive Regression Applied to a Large-Scale Collaborative Filtering Problem. Australasian Conference on Artificial Intelligence 2008: 435-446 | |
| 41 | Kathryn Hempstalk, Eibe Frank, Ian H. Witten: One-Class Classification by Combining Density and Class Probability Estimation. ECML/PKDD (1) 2008: 505-519 | |
| 40 | Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. FLAIRS Conference 2008: 318-319 | |
| 39 | Anna Huang, David N. Milne, Eibe Frank, Ian H. Witten: Clustering Documents with Active Learning Using Wikipedia. ICDM 2008: 839-844 | |
| 2007 | ||
| 38 | Ashraf M. Kibriya, Eibe Frank: An Empirical Comparison of Exact Nearest Neighbour Algorithms. PKDD 2007: 140-151 | |
| 2006 | ||
| 37 | Eibe Frank, Bernhard Pfahringer: Improving on Bagging with Input Smearing. PAKDD 2006: 97-106 | |
| 36 | Eibe Frank, Remco R. Bouckaert: Naive Bayes for Text Classification with Unbalanced Classes. PKDD 2006: 503-510 | |
| 2005 | ||
| 35 | Gabi Schmidberger, Eibe Frank: Unsupervised Discretization Using Tree-Based Density Estimation. PKDD 2005: 240-251 | |
| 34 | Marc Sumner, Eibe Frank, Mark A. Hall: Speeding Up Logistic Model Tree Induction. PKDD 2005: 675-683 | |
| 33 | Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. PKDD 2005: 84-95 | |
| 32 | Eibe Frank, Mark A. Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer: WEKA - A Machine Learning Workbench for Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 1305-1314 | |
| 31 | Yu Wang, Igor V. Tetko, Mark A. Hall, Eibe Frank, Axel Facius, Klaus F. X. Mayer, Hans-Werner Mewes: Gene selection from microarray data for cancer classification - a machine learning approach. Computational Biology and Chemistry 29(1): 37-46 (2005) | |
| 30 | Niels Landwehr, Mark Hall, Eibe Frank: Logistic Model Trees. Machine Learning 59(1-2): 161-205 (2005) | |
| 2004 | ||
| 29 | Peter Reutemann, Bernhard Pfahringer, Eibe Frank: A Toolbox for Learning from Relational Data with Propositional and Multi-instance Learners. Australian Conference on Artificial Intelligence 2004: 1017-1023 | |
| 28 | Ashraf M. Kibriya, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes: Multinomial Naive Bayes for Text Categorization Revisited. Australian Conference on Artificial Intelligence 2004: 488-499 | |
| 27 | Stefan Mutter, Mark Hall, Eibe Frank: Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining. Australian Conference on Artificial Intelligence 2004: 538-549 | |
| 26 | Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for multi-class problems. ICML 2004 | |
| 25 | Xin Xu, Eibe Frank: Logistic Regression and Boosting for Labeled Bags of Instances. PAKDD 2004: 272-281 | |
| 24 | Remco R. Bouckaert, Eibe Frank: Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms. PAKDD 2004: 3-12 | |
| 23 | Eibe Frank, Mark Hall, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten: Data mining in bioinformatics using Weka. Bioinformatics 20(15): 2479-2481 (2004) | |
| 22 | Eibe Frank, Gordon W. Paynter: Predicting Library of Congress classifications from Library of Congress subject headings. JASIST 55(3): 214-227 (2004) | |
| 2003 | ||
| 21 | Niels Landwehr, Mark Hall, Eibe Frank: Logistic Model Trees. ECML 2003: 241-252 | |
| 20 | Nils Weidmann, Eibe Frank, Bernhard Pfahringer: A Two-Level Learning Method for Generalized Multi-instance Problems. ECML 2003: 468-479 | |
| 19 | Eibe Frank, Mark Hall: Visualizing Class Probability Estimators. PKDD 2003: 168-179 | |
| 18 | Eibe Frank, Mark Hall, Bernhard Pfahringer: Locally Weighted Naive Bayes. UAI 2003: 249-256 | |
| 2002 | ||
| 17 | Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing Committees for Large Datasets. Discovery Science 2002: 153-164 | |
| 16 | Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall: Multiclass Alternating Decision Trees. ECML 2002: 161-172 | |
| 2001 | ||
| 15 | Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. ECML 2001: 145-156 | |
| 14 | Andrew Turpin, Eibe Frank, Mark Hall, Ian H. Witten, Chris A. Johnson: Determining Progression in Glaucoma Using Visual Fields. PAKDD 2001: 136-147 | |
| 13 | Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark Hall, Ian H. Witten: Interactive machine learning: letting users build classifiers. Int. J. Hum.-Comput. Stud. 55(3): 281-292 (2001) | |
| 2000 | ||
| 12 | Eibe Frank, Chang Chui, Ian H. Witten: Text Categorization Using Compression Models. Data Compression Conference 2000: 555 | |
| 11 | Stefan Kramer, Eibe Frank: Bottom-Up Propositionalization. ILP Work-in-progress reports 2000 | |
| 10 | Eibe Frank, Leonard E. Trigg, Geoffrey Holmes, Ian H. Witten: Naive Bayes for Regression (Technical Note). Machine Learning 41(1): 5-25 (2000) | |
| 1999 | ||
| 9 | Ian H. Witten, Eibe Frank: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations Morgan Kaufmann 1999 | |
| 8 | Ian H. Witten, Gordon W. Paynter, Eibe Frank, Carl Gutwin, Craig G. Nevill-Manning: KEA: Practical Automatic Keyphrase Extraction. ACM DL 1999: 254-255 | |
| 7 | Geoffrey Holmes, Mark Hall, Eibe Frank: Generating Rule Sets from Model Trees. Australian Joint Conference on Artificial Intelligence 1999: 1-12 | |
| 6 | Eibe Frank, Ian H. Witten: Making Better Use of Global Discretization. ICML 1999: 115-123 | |
| 5 | Eibe Frank, Gordon W. Paynter, Ian H. Witten, Carl Gutwin, Craig G. Nevill-Manning: Domain-Specific Keyphrase Extraction. IJCAI 1999: 668-673 | |
| 4 | Ian H. Witten, Gordon W. Paynter, Eibe Frank, Carl Gutwin, Craig G. Nevill-Manning: KEA: Practical Automatic Keyphrase Extraction CoRR cs.DL/9902007: (1999) | |
| 1998 | ||
| 3 | Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. ICML 1998: 144-151 | |
| 2 | Eibe Frank, Ian H. Witten: Using a Permutation Test for Attribute Selection in Decision Trees. ICML 1998: 152-160 | |
| 1 | Eibe Frank, Yong Wang, Stuart Inglis, Geoffrey Holmes, Ian H. Witten: Using Model Trees for Classification. Machine Learning 32(1): 63-76 (1998) | |