awesome-imbalanced-learning
github.com/zhiningliu1998/awesome-imbalanced-learning ↗😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切：论文、代码、框架与库
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me 3.2.3 slides resources from awesome-imbalanced-learning"
Installation instructions →What's inside
3.2 Github Repositories
- acm_imbalanced_learning3.2.3 Slides
slides and code for the ACM Imbalanced Learning talk on 27th April 2016 in Austin, TX.
- Advanced Machine Learning with scikit-learn: Imbalanced classification and text data3.2.1 Algorithms & Utilities & Jupyter Notebooks
Different approaches to feature selection, and resampling methods for imbalanced data.
- Anomaly Detection Learning Resources3.2.2 Paper list
Anomaly detection related books, papers, videos, and toolboxes.
- class_imbalance3.2.1 Algorithms & Utilities & Jupyter Notebooks
Jupyter Notebook presentation for class imbalance in binary classification.
- imbalanced-algorithms3.2.1 Algorithms & Utilities & Jupyter Notebooks
Python-based implementations of algorithms for learning on imbalanced data.
- imbalanced-dataset-sampler3.2.1 Algorithms & Utilities & Jupyter Notebooks
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
1.2 R
2.3 Data resampling
3.1 Datasets
Resources
1.3 Java
- KEEL
KEEL provides a simple
Showing a sample of 122 resources. View the full list on GitHub →