SMOClust

? Online machine learning in Python

Algorithms for outlier, adversarial and drift detection

? 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

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.

This is an official PyTorch implementation of the NeurIPS 2023 paper 《OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling》

MemStream: Memory-Based Streaming Anomaly Detection

This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).

CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system

A General Toolkit for Online Learning Approaches