Bernhard Pfahringer - Google Scholar Citations

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	All	Since 2015
Citations	32757	19583
h-index	48	40
i10-index	109	81

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Co-authors

Geoffrey HolmesVerified email at waikato.ac.nz
Eibe FrankProfessor, Department of Computer Science, University of WaikatoVerified email at cs.waikato.ac.nz
Albert BifetTélécom ParisTechVerified email at telecom-paristech.fr
Mark HallHonorary Research Associate, University of Waikato, New ZealandVerified email at cs.waikato.ac.nz
Ian H. WittenProfessor of Computer Science, University of Waikato, New ZealandVerified email at cs.waikato.ac.nz
Jesse ReadÉcole PolytechniqueVerified email at polytechnique.edu
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University MainzVerified email at informatik.uni-mainz.de
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Indrė ŽliobaitėUniversity of HelsinkiVerified email at helsinki.fi
Christoph Helmain silico toxicology gmbhVerified email at in-silico.ch
Ricard GavaldàUniversitat Politècnica de CatalunyaVerified email at cs.upc.edu
Felipe Bravo-MarquezAssistant Professor, University of ChileVerified email at dcc.uchile.cl
Hendrik BlockeelDepartment of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
Philipp KranenMicrosoft ResearchVerified email at microsoft.com
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Quan SunThe University of WaikatoVerified email at students.waikato.ac.nz
Jean Paul BarddalPrograma de Pós-Graduação em Informática (PPGIa), Pontifícia Universidade Católica do ParanáVerified email at ppgia.pucpr.br
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
Gerhard WidmerProfessor of Computer Science, Johannes Kepler University LinzVerified email at jku.at

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	20608	2009
Moa: Massive online analysis A Bifet, G Holmes, R Kirkby, B Pfahringer Journal of Machine Learning Research 11 (May), 1601-1604, 2010	1415	2010
Classifier chains for multi-label classification J Read, B Pfahringer, G Holmes, E Frank Machine learning 85 (3), 333, 2011	1233	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	638	2009
New ensemble methods for evolving data streams A Bifet, G Holmes, B Pfahringer, R Kirkby, R Gavaldà Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009	582	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	492	2009
Meta-Learning by Landmarking Various Learning Algorithms. B Pfahringer, H Bensusan, CG Giraud-Carrier ICML, 743-750, 2000	410	2000
Locally weighted naive bayes E Frank, M Hall, B Pfahringer Proceedings of the Nineteenth conference on Uncertainty in Artificial …, 2002	382	2002
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	368	2008
WEKAâˆ’Experiences with a Java Open-Source Project RR Bouckaert, E Frank, MA Hall, G Holmes, B Pfahringer, P Reutemann, ... Journal of Machine Learning Research 11 (Sep), 2533-2541, 2010	363	2010
Multinomial naive bayes for text categorization revisited AM Kibriya, E Frank, B Pfahringer, G Holmes Australasian Joint Conference on Artificial Intelligence, 488-499, 2004	339	2004
Winning the KDD99 classification cup: bagged boosting B Pfahringer ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000	269	2000
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	254	2013
Leveraging bagging for evolving data streams A Bifet, G Holmes, B Pfahringer Joint European conference on machine learning and knowledge discovery in …, 2010	218	2010
Multiclass alternating decision trees G Holmes, B Pfahringer, R Kirkby, E Frank, M Hall European Conference on Machine Learning, 161-172, 2002	205	2002
Meka: a multi-label/multi-target extension to weka J Read, P Reutemann, B Pfahringer, G Holmes The Journal of Machine Learning Research 17 (1), 667-671, 2016	189	2016
A two-level learning method for generalized multi-instance problems N Weidmann, E Frank, B Pfahringer European Conference on Machine Learning, 468-479, 2003	178	2003
New options for hoeffding trees B Pfahringer, G Holmes, R Kirkby Australasian Joint Conference on Artificial Intelligence, 90-99, 2007	162	2007
Prediction of ordinal classes using regression trees S Kramer, G Widmer, B Pfahringer, M De Groeve Fundamenta Informaticae 47 (1-2), 1-13, 2001	155	2001
andI M Hall, E Frank, G Holmes, B Pfahringer, P Reutemann H. Witten, The weka data mining software: An update, SIGKDD Explor. Newsl 11 …, 2009	142	2009

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