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 | 24957 | 2009 |
Classifier chains for multi-label classification J Read, B Pfahringer, G Holmes, E Frank Machine learning 85, 333-359, 2011 | 2345 | 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 | 2229 | 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 | 1037 | 2009 |
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 | 910 | 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 | 831 | 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 | 801 | 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 | 637 | 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 | 579 | 2008 |
Meta-Learning by Landmarking Various Learning Algorithms. B Pfahringer, H Bensusan, CG Giraud-Carrier ICML, 743-750, 2000 | 533 | 2000 |
Locally weighted naive bayes E Frank, M Hall, B Pfahringer arXiv preprint arXiv:1212.2487, 2012 | 498 | 2012 |
Regularisation of neural networks by enforcing lipschitz continuity H Gouk, E Frank, B Pfahringer, MJ Cree Machine Learning 110, 393-416, 2021 | 476 | 2021 |
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 | 463 | 2010 |
Leveraging bagging for evolving data streams A Bifet, G Holmes, B Pfahringer Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010 | 454 | 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 | 428 | 2013 |
Winning the KDD99 classification cup: bagged boosting B Pfahringer ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000 | 334 | 2000 |
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 | 330 | 2016 |
Machine learning for data streams: with practical examples in MOA A Bifet, R Gavalda, G Holmes, B Pfahringer MIT press, 2023 | 326 | 2023 |
Smote for regression L Torgo, RP Ribeiro, B Pfahringer, P Branco Portuguese conference on artificial intelligence, 378-389, 2013 | 324 | 2013 |
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 | 260 | 2002 |