load_gunpoint¶
- load_gunpoint(split=None, return_type='numpy3d')[source]¶
Load the GunPoint 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, 150) (return_type=”numpy3d”) or shape (n_cases, 150) (return_type=”numpy2d”), where n_cases is either 150 (split=”train” or “test”) or 300.
- y: np.ndarray
1D array of length 150 or 300. 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: 150 Train cases: 50 Test cases: 150 Number of classes: 2 Details: https://timeseriesclassification.com/description.php?Dataset=GunPoint
Examples
>>> from aeon.datasets import load_gunpoint >>> X, y = load_gunpoint()