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Dataset (Classification)

ItalyPowerDemand

API referenceSource

ItalyPowerDemand time series classification problem.

Example of a univariate problem with equal-length series.

Notes

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 was 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 October to March (inclusive) from April to September.

Dataset details: http://timeseriesclassification.com/description.php?Dataset=ItalyPowerDemand

Examples

>>> from sktime.datasets.classification import ItalyPowerDemand
>>> X, y = ItalyPowerDemand().load("X", "y")

Quickstart

python
from sktime.datasets.classification.italy_power_demand import ItalyPowerDemand

estimator = ItalyPowerDemand(return_mtype='pd-multiindex')

Examples

>>> from sktime.datasets.classification import ItalyPowerDemand
>>> X, y = ItalyPowerDemand (). load ("X", "y")