Bernhard Pfahringer
Bernhard Pfahringer
Professor of Computer Science, University of Waikato
Потвърден имейл адрес: waikato.ac.nz - Начална страница
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Позовавания
Година
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
209702009
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
14452010
Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine learning 85 (3), 333, 2011
12612011
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
6602009
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
5882009
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
4992009
Meta-Learning by Landmarking Various Learning Algorithms.
B Pfahringer, H Bensusan, CG Giraud-Carrier
ICML, 743-750, 2000
4252000
Locally weighted naive bayes
E Frank, M Hall, B Pfahringer
Proceedings of the Nineteenth conference on Uncertainty in Artificial …, 2002
3932002
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
3762008
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
3752010
Multinomial naive bayes for text categorization revisited
AM Kibriya, E Frank, B Pfahringer, G Holmes
Australasian Joint Conference on Artificial Intelligence, 488-499, 2004
3512004
Winning the KDD99 classification cup: bagged boosting
B Pfahringer
ACM SIGKDD Explorations Newsletter 1 (2), 65-66, 2000
2662000
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
2582013
Leveraging bagging for evolving data streams
A Bifet, G Holmes, B Pfahringer
Joint European conference on machine learning and knowledge discovery in …, 2010
2242010
Multiclass alternating decision trees
G Holmes, B Pfahringer, R Kirkby, E Frank, M Hall
European Conference on Machine Learning, 161-172, 2002
2052002
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
1972016
A two-level learning method for generalized multi-instance problems
N Weidmann, E Frank, B Pfahringer
European Conference on Machine Learning, 468-479, 2003
1792003
Witten. IH 2009
M Hall, E Frank, G Holmes, B Pfahringer, P Reutemann
The WEKA data mining software: An update, 0
166*
New options for hoeffding trees
B Pfahringer, G Holmes, R Kirkby
Australasian Joint Conference on Artificial Intelligence, 90-99, 2007
1622007
Prediction of ordinal classes using regression trees
S Kramer, G Widmer, B Pfahringer, M De Groeve
Fundamenta Informaticae 47 (1-2), 1-13, 2001
1582001
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