Cluster-based under-sampling approaches for imbalanced data distributions
For classification problem, the training data will significantly influence the classification accuracy. However, the data in real-world applications often are imbalanced class distribution, that is, most of the data are in majority class and little data are in minority class. In this case, if all th...
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Published in: | Expert systems with applications Vol. 36; no. 3; pp. 5718 - 5727 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier Ltd
01-04-2009
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Subjects: | |
Online Access: | Get full text |
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