Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
Guillaume Lemaître, Fernando Nogueira, Christos K. Aridas
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What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Scikit-learn: Machine Learning in Python | 2012 | 64,025 |
| SMOTE: Synthetic Minority Over-sampling Technique | 2002 | 32,402 |
| Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning | 2005 | 4,049 |
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Ann… | 2018 | 2,226 |
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Topics
| Imbalanced Data Classification Techniques | Computer Science |
| Machine Learning and Data Classification | Computer Science |
| Artificial Intelligence in Healthcare | Health Professions |
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