fetch_ucr

skfda.datasets.fetch_ucr(name: str, *, return_X_y: Literal[False] = False, **kwargs: Any) → Bunch

skfda.datasets.fetch_ucr(name: str, *, return_X_y: Literal[True], **kwargs: Any) → Tuple[FDataGrid, ndarray[Any, dtype[int64]]]

Fetch a dataset from the UCR/UEA repository.

The UCR/UEA Time Series Classification repository, hosted at www.timeseriesclassification.com includes plenty of classification problems with univariate and multivariate time series [1][2]. They are widely used in the functional data classification literature.

Parameters:

• name – Dataset name.

• return_X_y – Return tuple (data, target)

• kwargs – Additional parameters for the function skdatasets.repositories.ucr.fetch().

Returns:

The dataset requested.

Note

Functional multivariate datasets are not yet supported.

References

[1]

Hoang Anh Dau, Anthony Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, and Eamonn Keogh. The UCR time series archive. IEEE/CAA Journal of Automatica Sinica, 6(6):1293–1305, November 2019. doi:10.1109/JAS.2019.1911747.

[2]

Anthony Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, and Eamonn Keogh. The UEA multivariate time series classification archive, 2018. arXiv:1811.00075 [cs, stat], October 2018. URL: http://arxiv.org/abs/1811.00075 (visited on 2018-11-16), arXiv:1811.00075.

Examples using skfda.datasets.fetch_ucr

Getting the data

Getting the data