River: machine learning for streaming data in Python

2 code implementations • 8 Dec 2020 • Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphael Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes, Jesse Read, Talel Abdessalem, Albert Bifet

It is the result from the merger of the two most popular packages for stream learning in Python: Creme and scikit-multiflow.

BIG-bench Machine Learning Continual Learning

Adaptive XGBoost for Evolving Data Streams

1 code implementation • 15 May 2020 • Jacob Montiel, Rory Mitchell, Eibe Frank, Bernhard Pfahringer, Talel Abdessalem, Albert Bifet

The proposed method creates new members of the ensemble from mini-batches of data as new data becomes available.

General Classification

Scikit-Multiflow: A Multi-output Streaming Framework

1 code implementation • 12 Jul 2018 • Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem

Scikit-multiflow is a multi-output/multi-label and stream data mining framework for the Python programming language.

Pessimistic Uplift Modeling

no code implementations • 31 Mar 2016 • Atef Shaar, Talel Abdessalem, Olivier Segard

The experiments show that our approach outperforms the existing approaches, especially in the case of high noise data environment.