A method for resampling imbalanced datasets in binary classification tasks for real-world problems

Author:

Cateni Silvia,Colla Valentina,Vannucci Marco

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference36 articles.

1. A. Estabrooks, A combination scheme for inductive learning from imbalanced datasets (M.Sc. thesis), Faculty of Computer Science, Dalhousie University, 2000.

2. A multiple resampling method for learning from imbalanced dataset;Estabrooks;Comput. Intell.,2004

3. N. Japkowicz, The class imbalance problem: significance and strategies, in: Proceedings of the 2000 International Conference on Artificial Intelligence (IC-AI′2000): Special Track on Inductive Learning, Las Vegas, Nevada, 2000.

4. M. Pazzani, C. Marz, P. Murphy, K. Ali, T. Hume, C. Brunk, Reducing misclassification cost, in: Proceedings of the 11th International Conference on Machine Learning, 1994.

5. P. Li, K.L. Chan, W. Fang, Hybrid Kernel Machine Ensemble for Imbalanced Data Sets, in: 18th International Conference on Pattern Recognition, IEEE, 2006.

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