Machine Learning for Data Streams with CapyMOA

doi:10.1007/978-3-032-06129-4_27

Machine Learning for Data Streams with CapyMOA

2026-01-01

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AI

Guilherme Weigert Cassales

DOI：10.1007/978-3-032-06129-4_27

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Abstract

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The exponential growth of data in recent decades has underscored the need for high-speed, real-time, and adaptive processing in machine learning. Data stream learning provides an effective framework to address this challenge. This article introduces CapyMOA, an open-source library designed specifically for data stream learning, offering powerful tools for building and deploying adaptive ML models. GitHub: https://github.com/adaptive-machine-learning/CapyMOA. Website: https://capymoa.org.

Keywords:

Open-source

Data Streams

Machine Learning

Concept Drift

Online Continual Learning

Semi-supervised Learning

Machine Learning for Data Streams with CapyMOA

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