A general framework for never-ending learning from time series streams

DOI10.1007/s10618-014-0388-4zbMath1405.68281OpenAlexW1974283736MaRDI QIDQ1715913

Bing Hu, Jesin Zakaria, Yanping Chen, Thanawin Rakthanmanon, Yuan Hao, Eamonn J. Keogh

Publication date: 29 January 2019

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-014-0388-4

zbMATH Keywords

classificationtime seriesdata streamsnever-ending learning

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Domain agnostic online semantic segmentation for multi-dimensional time series ⋮ Classification of streaming time series under more realistic assumptions

Uses Software

• UCI-ml
• PhysioToolkit
• UCR Suite

Cites Work

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• Classification of streaming time series under more realistic assumptions
• Active Learning
• Markov Chains
• Database Theory - ICDT 2005
• An algorithm for information structuring and retrieval

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