sktime.datasets.base.load_basic_motions

sktime.datasets.base.load_basic_motions(split=None, return_X_y=False)[source]

Loads the BasicMotions time series classification problem and returns X and y.

Parameters
  • split (None or str{"train", "test"}, optional (default=None)) – Whether to load the train or test partition of the problem. By default it loads both.

  • return_X_y (bool, optional (default=False)) – If True, returns (features, target) separately instead of a single dataframe with columns for features and the target.

Returns

  • X (pandas DataFrame with m rows and c columns) – The time series data for the problem with m cases and c dimensions

  • y (numpy array) – The class labels for each case in X

  • Details

  • ——-

  • Dimensionality (univariate)

  • Series length (100)

  • Train cases (40)

  • Test cases (40)

  • Number of classes (4)

  • The data was generated as part of a student project where four students performed

  • four activities whilst wearing a smart watch. The watch collects 3D accelerometer

  • and a 3D gyroscope It consists of four classes, which are walking, resting,

  • running and badminton. Participants were required to record motion a total of

  • five times, and the data is sampled once every tenth of a second, for a ten second

  • period.

  • Dataset details (http://www.timeseriesclassification.com/description.php?Dataset)

  • =BasicMotions