A weighted pattern matching approach for classification of imbalanced data with a fireworks-based algorithm for feature selection
Learning a classifier from imbalanced data is a challenging problem in Machine learning. A dataset is said to be imbalanced when the number of instances belonging to one class is much less than the number of instances belonging to the other class. Classifiers that proves efficient on standard data f...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2019-04-01
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| Series: | Connection Science |
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| Online Access: | http://dx.doi.org/10.1080/09540091.2018.1512558 |