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sktime: A Unified Interface for Machine Learning with Time Series

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arxiv 1909.07872 v1 pith:MY344Z5F submitted 2019-09-17 cs.LG stat.ML

Markus Löning , Anthony Bagnall , Sajaysurya Ganesh , Viktor Kazakov , Jason Lines , Franz J. Király This is my paper · ORCID
classification cs.LGstat.ML
keywords seriestimeinterfacelearningsktimetasksunifiedmachine
verification ladder T0 review T1 audit T2 compute T3 formal
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We present sktime -- a new scikit-learn compatible Python library with a unified interface for machine learning with time series. Time series data gives rise to various distinct but closely related learning tasks, such as forecasting and time series classification, many of which can be solved by reducing them to related simpler tasks. We discuss the main rationale for creating a unified interface, including reduction, as well as the design of sktime's core API, supported by a clear overview of common time series tasks and reduction approaches.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 179 citations worldwide. Full citation record

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