Learning multivariate shapelets with multi-layer neural networks for interpretable time-series classification

DOI10.1007/s11634-021-00437-8zbMath1491.68185OpenAlexW3135149107MaRDI QIDQ2673346

Tom Dhaene, Dirk Deschrijver, Roberto Medico, Joeri Ruyssinck

Publication date: 9 June 2022

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-021-00437-8

zbMATH Keywords

neural networksmachine learningtime-series classificationshapelets

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Artificial neural networks and deep learning (68T07)

Uses Software

• Adam
• t-SNE
• GitHub
• tslearn
• sktime

Cites Work

• Classification of time series by shapelet transformation
• A time series forest for classification and feature extraction
• Generalized random shapelet forests
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