A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

😎 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

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库

Synthetic Minority Over-Sampling Technique for Regression

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架

An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems

Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)

Python-based implementations of algorithms for learning on imbalanced data.

Code repository for the online course Machine Learning with Imbalanced Data

[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond

[NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题

Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.

Papers about long-tailed tasks

datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries

A general, feasible, and extensible framework for classification tasks.

ResLT: Residual Learning for Long-tailed Recognition (TPAMI 2022)