sktime: A Unified Interface for Machine Learning with Time Series
This library solves the problem of fragmented tools for time series analysis for researchers and practitioners, though it is incremental as it builds on existing scikit-learn compatibility.
The authors introduced sktime, a scikit-learn compatible Python library that provides a unified interface for machine learning with time series, addressing tasks like forecasting and classification by reducing them to simpler problems.
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.