River: machine learning for streaming data in Python - Archive ouverte HAL
Article Dans Une Revue Journal of Machine Learning Research Année : 2021

River: machine learning for streaming data in Python

Résumé

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 scikitmultiflow. River introduces a revamped architecture based on the lessons learnt from the seminal packages. River’s ambition is to be the go-to library for doing machine learning on streaming data. Additionally, this open source package brings under the same umbrella a large community of practitioners and researchers. The source code is available at https://github.com/online-ml/river.

Dates et versions

hal-04468415 , version 1 (20-02-2024)

Identifiants

Citer

Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphaël Sourty, et al.. River: machine learning for streaming data in Python. Journal of Machine Learning Research, 2021, 22, pp.1-8. ⟨hal-04468415⟩
74 Consultations
0 Téléchargements

Altmetric

Partager

More