load_plaid¶
- load_plaid(split=None)[source]¶
Load the PLAID univariate time series classification problem.
Example of a univariate problem with unequal length time series.
- 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.
- Returns:
- X: list of 2D np.ndarray, one for each series.
- y: 1D numpy array of length len(X). The class labels for each time series
- instance in X.
Notes
Dimensionality: univariate Series length: variable Train cases: 537 Test cases: 537 Number of classes: 2 Details: https://timeseriesclassification.com/description.php?Dataset=PLAID
Examples
>>> from aeon.datasets import load_plaid >>> X, y = load_plaid()