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ORCID2nd LIDTA 2018: Dublin, Ireland
- Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA@ECML/PKDD 2018, Dublin, Ireland, September 10, 2018. Proceedings of Machine Learning Research 94, PMLR 2018
Preface
- Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco:
2nd Workshop on Learning with Imbalanced Domains: Preface. 1-7
Papers
- Jessa Bekker, Jesse Davis:
Learning from Positive and Unlabeled Data under the Selected At Random Assumption. 8-22 - Martha Roseberry, Alberto Cano:
Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams. 23-37 - Jordan Fréry, Amaury Habrard, Marc Sebban, Liyun He-Guelton:
Non-Linear Gradient Boosting for Class-Imbalance Learning. 38-51 - Alexander Hepburn, Ryan McConville, Raúl Santos-Rodríguez, Jesús Cid-Sueiro, Dario García-García:
Proper Losses for Learning with Example-Dependent Costs. 52-66 - Paula Branco, Luís Torgo, Rita P. Ribeiro:
REBAGG: REsampled BAGGing for Imbalanced Regression. 67-81 - Pawel Ksieniewicz
:
Undersampled Majority Class Ensemble for highly imbalanced binary classification. 82-94 - Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski:
ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. 95-109 - André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista:
On the Need of Class Ratio Insensitive Drift Tests for Data Streams. 110-124
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