River: Machine learning for streaming data in Python

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Title

River: Machine learning for streaming data in Python

Content partner

University of Waikato

Collection

ResearchCommons@Waikato

Description

River is a machine learning library for dynamic data streams and continual learning. It provides multiple state-of-the-art learning methods, data generators/transformers, performance metrics and evaluators for different stream learning problems. It is the result from the merger of two popular packages for stream learning in Python: Creme and scikit- multiow. River introduces a revamped architecture based on the lessons learnt from the seminal packages. River's ambition is to be the go-to libr...

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Format

Research Paper

Research format

Journal article

Date created

2021

Creator

Montiel, Jacob / Halford, Max / Mastelini, Saulo Martiello / Bolmier, Geoffrey / Sourty, Raphael / Vaysse, Robin / Zouitine, Adil / Gomes, Heitor Murilo / Read, Jesse / Abdessalem, Talel / Bifet, Albert

URL

https://hdl.handle.net/10289/14402

Related subjects

stream learning / online learning / data stream / concept drift / supervised learning / unsupervised learning / Python / computer science / Machine learning

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