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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
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
249012009
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine learning 85, 333-359, 2011
23142011
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
22182010
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009
10342009
The WEKA data mining software: an update, SIGKDD Explor
M Hall, E Frank, G Holmes, B Pfahringer, P Reutemann, IH Witten
Newsl 11 (1), 10-18, 2009
9092009
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
8252009
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
7962010
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
6322005
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
5752008
Meta-Learning by Landmarking Various Learning Algorithms.
B Pfahringer, H Bensusan, CG Giraud-Carrier
ICML, 743-750, 2000
5312000
Locally weighted naive bayes
E Frank, M Hall, B Pfahringer
arXiv preprint arXiv:1212.2487, 2012
4972012
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
4612010
Regularisation of neural networks by enforcing lipschitz continuity
H Gouk, E Frank, B Pfahringer, MJ Cree
Machine Learning 110, 393-416, 2021
4602021
Leveraging bagging for evolving data streams
A Bifet, G Holmes, B Pfahringer
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
4482010
Active learning with drifting streaming data
I ®liobaitė, A Bifet, B Pfahringer, G Holmes
IEEE transactions on neural networks and learning systems 25 (1), 27-39, 2013
4252013
Winning the KDD99 classification cup: bagged boosting
B Pfahringer
ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000
3302000
Meka: a multi-label/multi-target extension to weka
J Read, P Reutemann, B Pfahringer, G Holmes
Journal of Machine Learning Research 17 (21), 1-5, 2016
3292016
Machine learning for data streams: with practical examples in MOA
A Bifet, R Gavalda, G Holmes, B Pfahringer
MIT press, 2023
3202023
Smote for regression
L Torgo, RP Ribeiro, B Pfahringer, P Branco
Portuguese conference on artificial intelligence, 378-389, 2013
3122013
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
2582002
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