😎 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
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
[Github][Documentation][Gallery][Paper]; imbalanced-ensemble is a Python toolbox for quick implementing and deploying ensemble learning algorithms on class-imbalanced data. It is featured for:; (i) Unified, easy-to-use APIs, detailed documentation and examples.; (ii) Capable for multi-class…
[Github][Documentation][Paper]; imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance. It is compatible with scikit-learn and is part of scikit-learn-contrib projects.; Currently (v0.8.0), it includes 21…
[Documentation][Github] - A collection of 85 minority over-sampling techniques for imbalanced learning with multi-class oversampling and model selection features (All writen in Python, also support R and Julia).
[Documentation][Github] - A collection of 85 minority over-sampling techniques for imbalanced learning with multi-class oversampling and model selection features (All writen in Python, also support R and Julia).
[Documentation][Github] - Contains the implementation of Random under/over-sampling.
[Documentation] - Contains the implementation of ROSE (Random Over-Sampling Examples).
[Documentation] - Contains the implementation of SMOTE (Synthetic Minority Over-sampling TEchnique).
[Github][Paper] - KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms. This tool includes many widely used…
[Documentation][Github] - A Scala library for under-sampling and their ensemble variants in imbalanced classification.
[Documentation][Github] - A collection of 85 minority over-sampling techniques for imbalanced learning with multi-class oversampling and model selection features (All writen in Python, also support R and Julia).
Python-based implementations of algorithms for learning on imbalanced data.
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Jupyter Notebook presentation for class imbalance in binary classification.
Perform multi-class classification on imbalanced 20-news-group dataset.
Different approaches to feature selection, and resampling methods for imbalanced data.
by yzhao062 - Anomaly detection related books, papers, videos, and toolboxes.
Imbalanced Time-series Classification
slides and code for the ACM Imbalanced Learning talk on 27th April 2016 in Austin, TX.
Free cross-platform search engine indexing 50,000+ tutorials from Udemy, Skillshare, Pluralsight, and other major learning platforms across 45+ categories.
hesreallyhim/awesome-claude-code
A hand-picked collection of the finest of resources for the most awesome of agents, Claude Code, the undisputed champion of coding companions, from the unstoppable team…
VoltAgent/awesome-agent-skills
A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.
josephmisiti/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
academic/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
analysis-tools-dev/static-analysis
⚙️ A curated list of static analysis (SAST) tools and linters for all programming languages, config files, build tools, and more. The focus is on tools which improve…