sktime swMATH ID: 35430 Software Authors: Markus Löning, Anthony Bagnall, Sajaysurya Ganesh, Viktor Kazakov, Jason Lines, Franz J. Király Description: 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. Homepage: https://arxiv.org/abs/1909.07872 Source Code: https://github.com/alan-turing-institute/sktime Dependencies: Python Related Software: Python; tslearn; Scikit; SciPy; Numba; NumPy; TensorFlow; GitHub; dtaidistance; Matplotlib; mcfly; GluonTS; pyts; Seglearn; MVTS-Data Toolkit; Orange; WEKA; TSFEL; TSdist; TSSEARCH Cited in: 2 Documents all top 5 Cited by 10 Authors 1 Bannai, Kenichi 1 Deschrijver, Dirk 1 Dhaene, Tom 1 Hatano, Kohei 1 Medico, Roberto 1 Ruyssinck, Joeri 1 Suehiro, Daiki 1 Takeda, Akiko 1 Takimoto, Eiji 1 Yamamoto, Shuji Cited in 2 Serials 1 Neural Computation 1 Advances in Data Analysis and Classification. ADAC Cited in 2 Fields 2 Statistics (62-XX) 2 Computer science (68-XX) Citations by Year