Jesse Read
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Classifier chains for multi-label classification
J Read, B Pfahringer, G Holmes, E Frank
Machine learning 85 (3), 333-359, 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
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
Adaptive random forests for evolving data stream classification
HM Gomes, A Bifet, J Read, JP Barddal, F Enembreck, B Pfharinger, ...
Machine Learning 106 (9), 1469-1495, 2017
Meka: a multi-label/multi-target extension to weka
J Read, P Reutemann, B Pfahringer, G Holmes
A pruned problem transformation method for multi-label classification
J Read
Proc. 2008 New Zealand Computer Science Research Student Conference (NZCSRS …, 2008
Scikit-multiflow: A multi-output streaming framework
J Montiel, J Read, A Bifet, T Abdessalem
The Journal of Machine Learning Research 19 (1), 2915-2914, 2018
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
Scalable and efficient multi-label classification for evolving data streams
J Read, A Bifet, G Holmes, B Pfahringer
Machine Learning 88 (1), 243-272, 2012
Batch-incremental versus instance-incremental learning in dynamic and evolving data
J Read, A Bifet, B Pfahringer, G Holmes
International symposium on intelligent data analysis, 313-323, 2012
Cooperative parallel particle filters for online model selection and applications to urban mobility
L Martino, J Read, V Elvira, F Louzada
Digital Signal Processing 60, 172-185, 2017
Scalable multi-label classification
J Read
University of Waikato, 2010
Machine learning for streaming data: state of the art, challenges, and opportunities
HM Gomes, J Read, A Bifet, JP Barddal, J Gama
ACM SIGKDD Explorations Newsletter 21 (2), 6-22, 2019
Evaluation methods and decision theory for classification of streaming data with temporal dependence
I Žliobaitė, A Bifet, J Read, B Pfahringer, G Holmes
Machine Learning 98 (3), 455-482, 2015
Efficient monte carlo methods for multi-dimensional learning with classifier chains
J Read, L Martino, D Luengo
Pattern Recognition 47 (3), 1535-1546, 2014
Pitfalls in benchmarking data stream classification and how to avoid them
A Bifet, J Read, I Žliobaitė, B Pfahringer, G Holmes
Joint European conference on machine learning and knowledge discovery in …, 2013
Independent doubly adaptive rejection Metropolis sampling within Gibbs sampling
L Martino, J Read, D Luengo
IEEE Transactions on Signal Processing 63 (12), 3123-3138, 2015
Efficient data stream classification via probabilistic adaptive windows
A Bifet, B Pfahringer, J Read, G Holmes
Proceedings of the 28th annual ACM symposium on applied computing, 801-806, 2013
Scalable multi-output label prediction: From classifier chains to classifier trellises
J Read, L Martino, PM Olmos, D Luengo
Pattern Recognition 48 (6), 2096-2109, 2015
A distributed particle filter for nonlinear tracking in wireless sensor networks
J Read, K Achutegui, J Miguez
Signal Processing 98, 121-134, 2014
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Artículos 1–20