[Second International Workshop on Learning with Imbalanced Domains: Theory and Applications Logo] Proceedings of Machine Learning Research

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Volume 94: Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 10 September 2018, ECML-PKDD, Dublin, Ireland

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Editors: Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco

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Contents:

Preface

2nd Workshop on Learning with Imbalanced Domains: Preface

Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:1-7

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Papers

Learning from Positive and Unlabeled Data under the Selected At Random Assumption

Jessa Bekker, Jesse Davis; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:8-22

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Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams

Martha Roseberry, Alberto Cano; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:23-37

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Non-Linear Gradient Boosting for Class-Imbalance Learning

Jordan Frery, Amaury Habrard, Marc Sebban, Liyun He-Guelton; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:38-51

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Proper Losses for Learning with Example-Dependent Costs

Alexander Hepburn, Ryan McConville, Raúl Santos-Rodríguezo, Jesús Cid-Sueiro, Dario García-García; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:52-66

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REBAGG: REsampled BAGGing for Imbalanced Regression

Paula Branco, Luis Torgo, Rita P. Ribeiro; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:67-81

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Undersampled Majority Class Ensemble for highly imbalanced binary classification

Pawel Ksieniewicz; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:82-94

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ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information

Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:95-109

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On the Need of Class Ratio Insensitive Drift Tests for Data Streams

André Maletzke, Denis Reis, Everton Cherman, Gustavo Batista; Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 94:110-124

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