2008 |
50 | EE | Stefan Mutter,
Bernhard Pfahringer,
Geoffrey Holmes:
Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis.
Australasian Conference on Artificial Intelligence 2008: 278-288 |
49 | EE | Xing Wu,
Geoffrey Holmes,
Bernhard Pfahringer:
Mining Arbitrarily Large Datasets Using Heuristic k-Nearest Neighbour Search.
Australasian Conference on Artificial Intelligence 2008: 355-361 |
48 | EE | Jesse Read,
Bernhard Pfahringer,
Geoffrey Holmes:
Multi-label Classification Using Ensembles of Pruned Sets.
ICDM 2008: 995-1000 |
47 | EE | Joaquin Vanschoren,
Hendrik Blockeel,
Bernhard Pfahringer,
Geoffrey Holmes:
Organizing the World's Machine Learning Information.
ISoLA 2008: 693-708 |
46 | EE | Bernhard Pfahringer,
Geoffrey Holmes,
Richard Kirkby:
Handling Numeric Attributes in Hoeffding Trees.
PAKDD 2008: 296-307 |
45 | EE | Grant Anderson,
Bernhard Pfahringer:
Exploiting Propositionalization Based on Random Relational Rules for Semi-supervised Learning.
PAKDD 2008: 494-502 |
44 | EE | Joaquin Vanschoren,
Bernhard Pfahringer,
Geoffrey Holmes:
Learning from the Past with Experiment Databases.
PRICAI 2008: 485-496 |
2007 |
43 | EE | Bernhard Pfahringer,
Geoffrey Holmes,
Richard Kirkby:
New Options for Hoeffding Trees.
Australian Conference on Artificial Intelligence 2007: 90-99 |
42 | EE | Grant Anderson,
Bernhard Pfahringer:
Clustering Relational Data Based on Randomized Propositionalization.
ILP 2007: 39-48 |
41 | EE | Bernhard Pfahringer,
Claire Leschi,
Peter Reutemann:
Scaling Up Semi-supervised Learning: An Efficient and Effective LLGC Variant.
PAKDD 2007: 236-247 |
2006 |
40 | EE | Kurt Driessens,
Peter Reutemann,
Bernhard Pfahringer,
Claire Leschi:
Using Weighted Nearest Neighbor to Benefit from Unlabeled Data.
PAKDD 2006: 60-69 |
39 | EE | Eibe Frank,
Bernhard Pfahringer:
Improving on Bagging with Input Smearing.
PAKDD 2006: 97-106 |
2005 |
38 | | Stefan Kramer,
Bernhard Pfahringer:
Inductive Logic Programming, 15th International Conference, ILP 2005, Bonn, Germany, August 10-13, 2005, Proceedings
Springer 2005 |
37 | | Geoffrey Holmes,
Bernhard Pfahringer,
Richard Kirkby:
Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams.
CITA 2005: 130-36 |
36 | EE | Geoffrey Holmes,
Richard Kirkby,
Bernhard Pfahringer:
Stress-Testing Hoeffding Trees.
PKDD 2005: 495-502 |
35 | | 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 |
2004 |
34 | EE | 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 |
33 | EE | Mi Li,
Geoffrey Holmes,
Bernhard Pfahringer:
Clustering Large Datasets Using Cobweb and K-Means in Tandem.
Australian Conference on Artificial Intelligence 2004: 368-379 |
32 | EE | Ashraf M. Kibriya,
Eibe Frank,
Bernhard Pfahringer,
Geoffrey Holmes:
Multinomial Naive Bayes for Text Categorization Revisited.
Australian Conference on Artificial Intelligence 2004: 488-499 |
31 | EE | Hendrik Blockeel,
Saso Dzeroski,
Boris Kompare,
Stefan Kramer,
Bernhard Pfahringer,
Wim Van Laer:
Experiments In Predicting Biodegradability.
Applied Artificial Intelligence 18(2): 157-181 (2004) |
30 | EE | Bernhard Pfahringer:
The Weka solution to the 2004 KDD Cup.
SIGKDD Explorations 6(2): 117-119 (2004) |
2003 |
29 | EE | Nils Weidmann,
Eibe Frank,
Bernhard Pfahringer:
A Two-Level Learning Method for Generalized Multi-instance Problems.
ECML 2003: 468-479 |
28 | EE | Maximilien Sauban,
Bernhard Pfahringer:
Text Categorisation Using Document Profiling.
PKDD 2003: 411-422 |
27 | | Eibe Frank,
Mark Hall,
Bernhard Pfahringer:
Locally Weighted Naive Bayes.
UAI 2003: 249-256 |
2002 |
26 | EE | Geoffrey Holmes,
Bernhard Pfahringer,
Richard Kirkby,
Eibe Frank,
Mark Hall:
Multiclass Alternating Decision Trees.
ECML 2002: 161-172 |
25 | EE | Roger Clayton,
John G. Cleary,
Bernhard Pfahringer,
Mark Utting:
Tabling Structures for Bottom-Up Logic Programming.
LOPSTR 2002: 50-51 |
2001 |
24 | EE | Bernhard Pfahringer,
Geoffrey Holmes,
Gabi Schmidberger:
Wrapping Boosters against Noise.
Australian Joint Conference on Artificial Intelligence 2001: 402-413 |
23 | EE | Bernhard Pfahringer,
Geoffrey Holmes,
Richard Kirkby:
Optimizing the Induction of Alternating Decision Trees.
PAKDD 2001: 477-487 |
22 | | Stefan Kramer,
Gerhard Widmer,
Bernhard Pfahringer,
Michael de Groeve:
Prediction of Ordinal Classes Using Regression Trees.
Fundam. Inform. 47(1-2): 1-13 (2001) |
2000 |
21 | | Johannes Fürnkranz,
Bernhard Pfahringer,
Hermann Kaindl,
Stefan Kramer:
Learning to Use Operational Advice.
ECAI 2000: 291-295 |
20 | | Bernhard Pfahringer,
Hilan Bensusan,
Christophe G. Giraud-Carrier:
Meta-Learning by Landmarking Various Learning Algorithms.
ICML 2000: 743-750 |
19 | EE | Stefan Kramer,
Gerhard Widmer,
Bernhard Pfahringer,
Michael de Groeve:
Prediction of Ordinal Classes Using Regression Trees.
ISMIS 2000: 426-434 |
18 | EE | Klaus Kovar,
Johannes Fürnkranz,
Johann Petrak,
Bernhard Pfahringer,
Robert Trappl,
Gerhard Widmer:
Searching for Patterns in Political Event Sequences: Experiments with the Keds Database.
Cybernetics and Systems 31(6): 649-668 (2000) |
17 | EE | Bernhard Pfahringer:
Winning the KDD99 Classification Cup: Bagged Boosting.
SIGKDD Explorations 1(2): 65-66 (2000) |
1999 |
16 | EE | Saso Dzeroski,
Hendrik Blockeel,
Boris Kompare,
Stefan Kramer,
Bernhard Pfahringer,
Wim Van Laer:
Experiments in Predicting Biodegradability.
ILP 1999: 80-91 |
1998 |
15 | | Stefan Kramer,
Bernhard Pfahringer,
Christopher Helma:
Stochastic Propositionalization of Non-determinate Background Knowledge.
ILP 1998: 80-94 |
14 | EE | Johannes Fürnkranz,
Bernhard Pfahringer:
Guest Editorial: First-Order Knowledge Discovery in Databases.
Applied Artificial Intelligence 12(5): 345-361 (1998) |
1997 |
13 | | Bernhard Pfahringer:
Compression-Based Pruning of Decision Lists.
ECML 1997: 199-212 |
12 | | Stefan Kramer,
Bernhard Pfahringer,
Christoph Helma:
Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail.
KDD 1997: 223-226 |
1996 |
11 | | Stefan Kramer,
Bernhard Pfahringer:
Efficient Search for Strong Partial Determinations.
KDD 1996: 371-374 |
1995 |
10 | | Bernhard Pfahringer:
A New MDL Measure for Robust Rule Induction (Extended Abstract).
ECML 1995: 331-334 |
9 | | Bernhard Pfahringer:
Compression-Based Discretization of Continuous Attributes.
ICML 1995: 456-463 |
8 | | Bernhard Pfahringer,
Stefan Kramer:
Compression-Based Evaluation of Partial Determinations.
KDD 1995: 234-239 |
1994 |
7 | | Bernhard Pfahringer:
Controlling Constructive Induction in CIPF: An MDL Approach.
ECML 1994: 242-256 |
6 | | Bernhard Pfahringer:
Robust Constructive Induction.
KI 1994: 118-129 |
1992 |
5 | | Bernhard Pfahringer:
The Logical Way to Build a DL-based KR System.
Description Logics 1992: 76-77 |
1991 |
4 | | Ernst Buchberger,
Elizabeth Garner,
Wolfgang Heinz,
Johannes Matiasek,
Bernhard Pfahringer:
VIE-DU: Dialogue by Unification.
ÖGAI 1991: 42-51 |
1989 |
3 | | Bernhard Pfahringer:
Extending Explanation-Based Generalization.
ÖGAI 1989: 149-153 |
1988 |
2 | | Bernhard Pfahringer,
M. Hoberstorfer,
Robert Trappl:
A decision support system for village health workers in developing countries.
Applied Artificial Intelligence 2(1): 47-63 (1988) |
1985 |
1 | | Bernhard Pfahringer,
Christian Holzbaur:
VIE-KET: Frames + Prolog.
ÖGAI 1985: 132-139 |