sktime.datasets.base
.load_acsf1¶
-
sktime.datasets.base.
load_acsf1
(split=None, return_X_y=False)[source]¶ Loads the power consumption of typical appliances 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 (1460)
Train cases (100)
Test cases (100)
Number of classes (10)
The dataset contains the power consumption of typical appliances.
The recordings are characterized by long idle periods and some high bursts
of energy consumption when the appliance is active.
The classes correspond to 10 categories of home appliances;
mobile phones (via chargers), coffee machines, computer stations
(including monitor), fridges and freezers, Hi-Fi systems (CD players),
lamp (CFL), laptops (via chargers), microwave ovens, printers, and
televisions (LCD or LED).”
Dataset details (http://www.timeseriesclassification.com/description.php?Dataset)
=ACSF1