Radulovic, NedeljkoBoulegane, DihiaBifet, Albert2026-08-112026-08-112020Radulovic, N., Boulegane, D., & Bifet, A. (2020). SCALAR - A platform for real-time machine learning competitions on data streams. Journal of Open Source Software, 5(56), 2676-2676. https://doi.org/10.21105/joss.026762475-9066https://hdl.handle.net/10289/18528SCALAR is a new platform for running real-time machine learning competitions on data streams. Following the intent of Kaggle, which serves as a platform for organizing machine learning competitions adapted for batch learning, we propose SCALAR as a novel platform explicitly designed for stream learning in real-time. SCALAR supports both classification and regression problems in the data streaming setting. It has been developed in Python, using state of the art open-source solutions: Apache Kafka, Apache Spark, gRPC, Protobuf, and Docker.SCALAR is a new platform for running real-time machine learning competitions on data streams. Following the intent of Kaggle, which serves as a platform for organizing machine learning competitions adapted for batch learning, we propose SCALAR as a novel platform explicitly designed for stream learning in real-time. SCALAR supports both classification and regression problems in the data streaming setting. It has been developed in Python, using state of the art open-source solutions: Apache Kafka, Apache Spark, gRPC, Protobuf, and Docker.enAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/computer scienceJournal Article10.21105/joss.026762475-906646 Information and Computing Sciences46 Information and computing sciences