Bernhard Pfahringer

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Geoffrey HolmesUniversity of WaikatoVerified email at waikato.ac.nz
Eibe FrankProfessor, Department of Computer Science, University of WaikatoVerified email at cs.waikato.ac.nz
Albert BifetTélécom ParisTech & University of WaikatoVerified email at telecom-paristech.fr
Mark HallHonorary Research Associate, University of Waikato, New ZealandVerified email at cs.waikato.ac.nz
Jesse ReadÉcole PolytechniqueVerified email at polytechnique.edu
Ian H. WittenProfessor of Computer Science, University of Waikato, New ZealandVerified email at waikato.ac.nz
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University MainzVerified email at informatik.uni-mainz.de
Philipp KranenMicrosoft ResearchVerified email at microsoft.com
Thomas SeidlProfessor of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), GermanyVerified email at dbs.ifi.lmu.de
Hardy KremerDeloitte Analytics Institute, GermanyVerified email at deloitte.de
Indrė ŽliobaitėUniversity of HelsinkiVerified email at helsinki.fi
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Christoph Helmain silico toxicology gmbhVerified email at in-silico.ch
Heitor Murilo GomesSenior Research Fellow, Department of Computer Science, University of WaikatoVerified email at waikato.ac.nz
Felipe Bravo-MarquezAssistant Professor, University of ChileVerified email at dcc.uchile.cl
Henry GoukPostdoctoral Research Associate, University of EdinburghVerified email at inf.ed.ac.uk
Ricard GavaldàUniversitat Politècnica de Catalunya + Amalfi AnalyticsVerified email at cs.upc.edu
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Jean Paul BarddalPrograma de Pós-Graduação em Informática (PPGIa), Pontifícia Universidade Católica do ParanáVerified email at ppgia.pucpr.br
Michael MayoUniversity of WaikatoVerified email at waikato.ac.nz

Bernhard Pfahringer

Professor of Computer Science, University of Waikato

Verified email at waikato.ac.nz - Homepage

Machine Learning Data Mining


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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	23777	2009
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	1855	2010
Classifier chains for multi-label classification J Read, B Pfahringer, G Holmes, E Frank Machine learning 85 (3), 333-359, 2011	1796	2011
Classifier chains for multi-label classification J Read, B Pfahringer, G Holmes, E Frank Joint European conference on machine learning and knowledge discovery in …, 2009	861	2009
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	714	2009
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, 2009	653	2009
Meta-Learning by Landmarking Various Learning Algorithms. B Pfahringer, H Bensusan, CG Giraud-Carrier ICML, 743-750, 2000	496	2000
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	485	2008
Multinomial naive bayes for text categorization revisited AM Kibriya, E Frank, B Pfahringer, G Holmes Australasian Joint Conference on Artificial Intelligence, 488-499, 2004	483	2004
Locally weighted naive bayes E Frank, M Hall, B Pfahringer arXiv preprint arXiv:1212.2487, 2012	447	2012
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	410	2010
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	344	2013
Leveraging bagging for evolving data streams A Bifet, G Holmes, B Pfahringer Joint European conference on machine learning and knowledge discovery in …, 2010	334	2010
Winning the KDD99 classification cup: bagged boosting B Pfahringer ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000	314	2000
Meka: a multi-label/multi-target extension to weka J Read, P Reutemann, B Pfahringer, G Holmes	269	2016
Multiclass alternating decision trees G Holmes, B Pfahringer, R Kirkby, E Frank, M Hall European Conference on Machine Learning, 161-172, 2002	232	2002
Regularisation of neural networks by enforcing lipschitz continuity H Gouk, E Frank, B Pfahringer, MJ Cree Machine Learning 110 (2), 393-416, 2021	227	2021
A two-level learning method for generalized multi-instance problems N Weidmann, E Frank, B Pfahringer European Conference on Machine Learning, 468-479, 2003	203	2003
New options for hoeffding trees B Pfahringer, G Holmes, R Kirkby Australasian Joint Conference on Artificial Intelligence, 90-99, 2007	194	2007
Machine learning for data streams: with practical examples in MOA A Bifet, R Gavalda, G Holmes, B Pfahringer MIT press, 2018	187	2018

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