load_arrow_head¶

load_arrow_head(split=None, return_type='numpy3d')[source]¶

Load the ArrowHead univariate time series classification problem.

Parameters:

split: None or one of “TRAIN”, “TEST”, default=None: Whether to load the train or test instances of the problem. By default it loads both train and test instances into a single array.
return_type: string, default=”numpy3d”: Data structure to use for time series, should be either “numpy2d” or “numpy3d”.

Returns:

X:np.ndarray: shape (n_cases, 1, 251) (if return_type=”numpy3d”) or shape (n_cases, 251) (return_type=”numpy2d”), where n_cases where n_cases is either 36 (split = “train”), 175 (split=”test”) or 211.
y: np.ndarray: 1D array of length 36, 175 or 211. The class labels for each time series instance in X.

Raises:

ValueError is raised if the data cannot be stored in the requested return_type.

Notes

Dimensionality: univariate Series length: 251 Train cases: 36 Test cases: 175 Number of classes: 3 Details: https://timeseriesclassification.com/description.php?Dataset=ArrowHead

Examples

>>> from aeon.datasets import load_arrow_head
>>> X, y = load_arrow_head()