2023/10/18 by Indrė Žliobaitė, Zliobaite, Indre, Jesse Read +1
Computer Science · #Data Stream Mining Techniques #Databases (cs.DB) #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Statistical and Computational Modeling #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2310.19811
openalex publication_date 2023/10/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Machine learning from data streams is an active and growing research area. Research on learning from streaming data typically makes strict assumptions linked to computational resource constraints, including requirements for stream mining algorithms to inspect each instance not more than once and be ready to give a prediction at any time. Here we review the historical context of data streams research placing the common assumptions used in machine learning over data streams in their historical context.