sktime: A Unified Interface for Machine Learning with Time Series. 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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References in zbMATH (referenced in 8 articles )
Showing results 1 to 8 of 8.
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- Alexandrov, Alexander; Benidis, Konstantinos; Bohlke-Schneider, Michael; Flunkert, Valentin; Gasthaus, Jan; Januschowski, Tim; Maddix, Danielle C.; Rangapuram, Syama; Salinas, David; Schulz, Jasper; Stella, Lorenzo; Türkmen, Ali Caner; Wang, Yuyang: GluonTS: probabilistic and neural time series modeling in Python (2020)
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- Suehiro, Daiki; Hatano, Kohei; Takimoto, Eiji; Yamamoto, Shuji; Bannai, Kenichi; Takeda, Akiko: Theory and algorithms for shapelet-based multiple-instance learning (2020)
- Tavenard, Romain; Faouzi, Johann; Vandewiele, Gilles; Divo, Felix; Androz, Guillaume; Holtz, Chester; Payne, Marie; Yurchak, Roman; Rußwurm, Marc; Kolar, Kushal; Woods, Eli: tslearn, a machine learning toolkit for time series data (2020)