Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series

DOI10.1007/s10618-014-0345-2zbMath1403.68190OpenAlexW1984713180WikidataQ59412822 ScholiaQ59412822MaRDI QIDQ1711225

Stefano Lonardi, Yuan Hao, Bing Hu, Thanawin Rakthanmanon, Scott R. Evans, Eamonn J. Keogh

Publication date: 17 January 2019

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

Full work available at URL: https://doi.org/10.1007/s10618-014-0345-2

zbMATH Keywords

time seriesdimensionality reductionMDL

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)

Greedy Gaussian segmentation of multivariate time series ⋮ The minimum description length principle for pattern mining: a survey

Uses Software

• vbFRET

Cites Work

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• Rate Distortion and Denoising of Individual Data Using Kolmogorov Complexity
• KI 2004: Advances in Artificial Intelligence
• An Information Measure for Classification

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