pyts.datasets.fetch_uea_dataset(dataset, use_cache=True, data_home=None, return_X_y=False)[source]

Fetch dataset from UEA TSC Archive by name.

Fetched data sets are saved by default in the pyts/datasets/cached_datasets/UEA/ folder. To avoid downloading the same data set several times, it is highly recommended not to change the default values of use_cache and path.

dataset : str

Name of the dataset.

use_cache : bool (default = True)

If True, look if the data set has already been fetched and load the fetched version if it is the case. If False, download the data set from the UCR Time Series Classification Archive.

data_home : None or str (default = None)

The path of the folder containing the cached data set. If None, the pyts.datasets.cached_datasets/UEA/ folder is used. If the data set is not found, it is downloaded and cached in this path.

return_X_y : bool (default = False)

If True, returns (data_train, data_test, target_train, target_test) instead of a Bunch object. See below for more information about the data and target object.

data : Bunch

Dictionary-like object, with attributes:

data_train : array of floats

The time series in the training set.

data_test : array of floats

The time series in the test set.

target_train : array of integers

The classification labels in the training set.

target_test : array of integers

The classification labels in the test set.

DESCR : str

The full description of the dataset.

url : str

The url of the dataset.

(data_train, data_test, target_train, target_test) : tuple if return_X_y is True


Missing values are represented as NaN’s.


[1]A. Bagnall et al, “The UEA multivariate time series classification archive, 2018”. arXiv:1811.00075 [cs, stat], 2018.
[2]A. Bagnall et al, “The UEA & UCR Time Series Classification Repository”,