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Learning in Dynamic Environments

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Learning from Data Streams in Dynamic Environments

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSAPPLSCIENCES))

Abstract

In this chapter, the problem of drifting data streams in dynamic environments is formalized, and its framework is defined. Then, the kinds and characteristics of the concept drift are presented. Finally, the real-world applications generating drifting data streams are discussed. The goal is to give a picture of the problem of learning from data streams in dynamic environments, its causes, sources, and characteristics in order to discuss later alternatives to solve this problem.

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Authors and Affiliations

  1. Computer Science and Automatic Control Department High National Engineering School of Mines, Douai, France

    Moamar Sayed-Mouchaweh

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  1. Moamar Sayed-Mouchaweh
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Sayed-Mouchaweh, M. (2016). Learning in Dynamic Environments. In: Learning from Data Streams in Dynamic Environments. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-25667-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-25667-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25665-8

  • Online ISBN: 978-3-319-25667-2

  • eBook Packages: EngineeringEngineering (R0)

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