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Bernhard Pfahringer
Bernhard Pfahringer
Professor of Computer Science, University of Waikato
Verified email at waikato.ac.nz - Homepage
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Cited by
Year
The WEKA data mining software: an update
M Hall, E Frank, G Holmes, B Pfahringer, P Reutemann, IH Witten
ACM SIGKDD explorations newsletter 11 (1), 10-18, 2009
242692009
Moa: Massive online analysis, a framework for stream classification and clustering
A Bifet, G Holmes, B Pfahringer, P Kranen, H Kremer, T Jansen, T Seidl
Proceedings of the first workshop on applications of pattern analysis, 44-50, 2010
20032010
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine learning 85, 333-359, 2011
19812011
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009
9192009
New ensemble methods for evolving data streams
A Bifet, G Holmes, B Pfahringer, R Kirkby, R Gavalda
Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009
7592009
Weka-a machine learning workbench for data mining
E Frank, M Hall, G Holmes, R Kirkby, B Pfahringer, IH Witten, L Trigg
Data mining and knowledge discovery handbook, 1269-1277, 2010
7082010
Multinomial naive bayes for text categorization revisited
AM Kibriya, E Frank, B Pfahringer, G Holmes
AI 2004: Advances in Artificial Intelligence: 17th Australian Joint …, 2005
5462005
Meta-Learning by Landmarking Various Learning Algorithms.
B Pfahringer, H Bensusan, CG Giraud-Carrier
ICML, 743-750, 2000
5172000
Multi-label classification using ensembles of pruned sets
J Read, B Pfahringer, G Holmes
2008 eighth IEEE international conference on data mining, 995-1000, 2008
5122008
Locally weighted naive bayes
E Frank, M Hall, B Pfahringer
arXiv preprint arXiv:1212.2487, 2012
4642012
WEKA---Experiences with a Java Open-Source Project
RR Bouckaert, E Frank, MA Hall, G Holmes, B Pfahringer, P Reutemann, ...
The Journal of Machine Learning Research 11, 2533-2541, 2010
4282010
Active learning with drifting streaming data
I Žliobaitė, A Bifet, B Pfahringer, G Holmes
IEEE transactions on neural networks and learning systems 25 (1), 27-39, 2013
3792013
Leveraging bagging for evolving data streams
A Bifet, G Holmes, B Pfahringer
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
3722010
Winning the KDD99 classification cup: bagged boosting
B Pfahringer
ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000
3212000
Regularisation of neural networks by enforcing lipschitz continuity
H Gouk, E Frank, B Pfahringer, MJ Cree
Machine Learning 110, 393-416, 2021
3012021
Meka: a multi-label/multi-target extension to weka
J Read, P Reutemann, B Pfahringer, G Holmes
2852016
Multiclass alternating decision trees
G Holmes, B Pfahringer, R Kirkby, E Frank, M Hall
Machine Learning: ECML 2002: 13th European Conference on Machine Learning …, 2002
2442002
Machine learning for data streams: with practical examples in MOA
A Bifet, R Gavalda, G Holmes, B Pfahringer
MIT press, 2018
2292018
A two-level learning method for generalized multi-instance problems
N Weidmann, E Frank, B Pfahringer
ECML 3, 468-479, 2003
2102003
New options for hoeffding trees
B Pfahringer, G Holmes, R Kirkby
AI 2007: Advances in Artificial Intelligence: 20th Australian Joint …, 2007
2082007
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