Predictive Handling of Asynchronous Concept Drifts in Distributed Environments

• Main Authors: ANG, Hock Hee, Gopalkrishnan, Vivek, Zliobaite, Indre, Pechenizkiy, Mykola, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Accuracy; Adaptation models; Classification; Data models; Detectors; Distributed databases; Predictive models; Training; concept drift; distributed systems; Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/2281; https://ink.library.smu.edu.sg/context/sis_research/article/3281/viewcontent/Predictive_Handling_of_Asynchronous_Concept_Drifts_in_Distributed_Environments.pdf
• Institution: Singapore Management University

In a distributed computing environment, peers collaboratively learn to classify concepts of interest from each other. When external changes happen and their concepts drift, the peers should adapt to avoid increase in misclassification errors. The problem of adaptation becomes more difficult when the...