sktime.datasets.base
.load_italy_power_demand¶
-
sktime.datasets.base.
load_italy_power_demand
(split=None, return_X_y=False)[source]¶ Loads the ItalyPowerDemand 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 (24)
Train cases (67)
Test cases (1029)
Number of classes (2)
The data was derived from twelve monthly electrical power demand time
series from Italy and
first used in the paper “Intelligent Icons (Integrating Lite-Weight Data)
Mining and
Visualization into GUI Operating Systems”. The classification task is to
distinguish days
from Oct to March (inclusive) from April to September.
Dataset details (http://timeseriesclassification.com/description.php)
?Dataset=ItalyPowerDemand