Name
Abstract | ||
|---|---|---|
Many real-world classification tasks suffer from the class imbalanced problem, in which some classes are highly underrepresented as compared to other classes. In this paper, we focus on multi-class imbalance problems which are considerably more difficult to address than two-class imbalanced problems. On this account, we develop a novel and effective procedure, called dynamic ensemble selection for multi-class imbalanced datasets (DES-MI), in which the competence of the candidate classifiers are assessed with weighted instances in the neighborhood. The proposed DES-MI consists of two key components: the generation of balanced training datasets and the selection of appropriate classifiers. To do so, we develop a preprocessing procedure to balance the training dataset which relies on random balance. To select the most appropriate classifiers in the scenario of multi-class imbalance problems, we propose a weighting mechanism to highlight the competence of classifiers that are more powerful in classifying examples in the region of underrepresented competence. We develop a thorough experimental study in order to verify the benefits of DES-MI in handling multi-class imbalanced datasets. The obtained results, supported by the proper statistical analysis, indicate that DES-MI is able to improve the classification performance for multi-class imbalanced datasets. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ins.2018.03.002 | Information Sciences |
Keywords | Field | DocType |
Multi-class classification,Imbalanced datasets,Multiple classifier system,Ensemble learning,Binary decomposition,Resampling techniques | Ensemble selection,Preprocessor,Imbalance problems,Artificial intelligence,A-weighting,Mathematics,Machine learning,Statistical analysis | Journal |
Volume | ISSN | Citations |
445 | 0020-0255 | 10 |
PageRank | References | Authors |
0.63 | 37 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salvador García | 1 | 4151 | 118.45 |
| Zhongliang Zhang | 2 | 14 | 2.02 |
| Abdulrahman H. Altalhi | 3 | 70 | 13.68 |
| Saleh Alshomrani | 4 | 108 | 10.21 |
| Francisco Herrera | 5 | 27391 | 1168.49 |