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