Bernhard Pfahringer

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Geoffrey HolmesUniversity of WaikatoEmail confirmado em waikato.ac.nz
Eibe FrankProfessor, Department of Computer Science, University of WaikatoEmail confirmado em cs.waikato.ac.nz
Albert BifetTélécom ParisTech & University of WaikatoEmail confirmado em telecom-paristech.fr
Mark HallHonorary Research Associate, University of Waikato, New ZealandEmail confirmado em cs.waikato.ac.nz
Ian H. WittenProfessor of Computer Science, University of Waikato, New ZealandEmail confirmado em waikato.ac.nz
Jesse ReadÉcole PolytechniqueEmail confirmado em polytechnique.edu
Stefan KramerProfessor of Computer Science, Johannes Gutenberg University MainzEmail confirmado em informatik.uni-mainz.de
Heitor Murilo GomesSenior Lecturer in AI, Victoria University of WellingtonEmail confirmado em vuw.ac.nz
Philipp KranenMicrosoft ResearchEmail confirmado em microsoft.com
Thomas SeidlProfessor of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), MCML, GermanyEmail confirmado em dbs.ifi.lmu.de
Hardy KremerDeloitte Analytics Institute, GermanyEmail confirmado em deloitte.de
Indrė ŽliobaitėProfessor, University of HelsinkiEmail confirmado em helsinki.fi
Henry GoukAssistant Professor, University of EdinburghEmail confirmado em ed.ac.uk
Joaquin VanschorenEindhoven University of TechnologyEmail confirmado em tue.nl
Felipe Bravo-MarquezAssociate Professor, University of ChileEmail confirmado em dcc.uchile.cl
Ricard GavaldàUniversitat Politècnica de Catalunya + Amalfi AnalyticsEmail confirmado em cs.upc.edu
Christoph Helmain silico toxicology gmbhEmail confirmado em in-silico.ch
Jean Paul BarddalPrograma de Pós-Graduação em Informática (PPGIa), Pontifícia Universidade Católica do Paraná (PUCPR)Email confirmado em ppgia.pucpr.br
Hendrik BlockeelDepartment of Computer Science, KU LeuvenEmail confirmado em cs.kuleuven.be
Jan N. van RijnLeiden UniversityEmail confirmado em liacs.leidenuniv.nl

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Bernhard Pfahringer

Professor of Computer Science, University of Waikato

Email confirmado em waikato.ac.nz - Página inicial

Machine Learning Data Mining


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
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	25445	2009
Classifier chains for multi-label classification J Read, B Pfahringer, G Holmes, E Frank Machine learning 85, 333-359, 2011	2470	2011
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	2291	2010
Classifier chains for multi-label classification J Read, B Pfahringer, G Holmes, E Frank Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009	1059	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	842	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, 2010	831	2010
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	676	2005
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	595	2008
Meta-Learning by Landmarking Various Learning Algorithms. B Pfahringer, H Bensusan, CG Giraud-Carrier ICML, 743-750, 2000	539	2000
Regularisation of neural networks by enforcing lipschitz continuity H Gouk, E Frank, B Pfahringer, MJ Cree Machine Learning 110, 393-416, 2021	527	2021
Locally weighted naive bayes E Frank, M Hall, B Pfahringer arXiv preprint arXiv:1212.2487, 2012	505	2012
Leveraging bagging for evolving data streams A Bifet, G Holmes, B Pfahringer Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010	472	2010
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	466	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	448	2013
Smote for regression L Torgo, RP Ribeiro, B Pfahringer, P Branco Portuguese conference on artificial intelligence, 378-389, 2013	376	2013
Machine learning for data streams: with practical examples in MOA A Bifet, R Gavalda, G Holmes, B Pfahringer MIT press, 2023	359	2023
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	334	2016
Winning the KDD99 classification cup: Bagged boosting B Pfahringer ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000	329	2000
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	266	2002
Efficient online evaluation of big data stream classifiers A Bifet, G de Francisci Morales, J Read, G Holmes, B Pfahringer Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015	233	2015

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