A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data
Class imbalance presents a major hurdle in the application of classification methods. A commonly taken approach is to learn ensembles of classifiers using rebalanced data. Examples include bootstrap averaging (bagging) combined with either undersampling or oversampling of the minority class examples...
| Main Authors: | , , |
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| Other Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV,
2019-02-28T18:46:09Z.
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| Subjects: | |
| Online Access: | Get fulltext |