ItalyPowerDemand

class ItalyPowerDemand(return_mtype='pd-multiindex')[source]

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")

Methods

`cache_files_directory`()	Get the directory where cache files are stored.
`cleanup_cache_files`()	Cleanup cache files from the cache directory.
`clone`()	Obtain a clone of the object with same hyper-parameters and config.
`clone_tags`(estimator[, tag_names])	Clone tags from another object as dynamic override.
`create_test_instance`([parameter_set])	Construct an instance of the class, using first test parameter set.
`create_test_instances_and_names`([parameter_set])	Create list of all test instances and a list of names for them.
`get_class_tag`(tag_name[, tag_value_default])	Get class tag value from class, with tag level inheritance from parents.
`get_class_tags`()	Get class tags from class, with tag level inheritance from parent classes.
`get_config`()	Get config flags for self.
`get_param_defaults`()	Get object's parameter defaults.
`get_param_names`([sort])	Get object's parameter names.
`get_params`([deep])	Get a dict of parameters values for this object.
`get_tag`(tag_name[, tag_value_default, ...])	Get tag value from instance, with tag level inheritance and overrides.
`get_tags`()	Get tags from instance, with tag level inheritance and overrides.
`get_test_params`([parameter_set])	Return testing parameter settings for the skbase object.
`is_composite`()	Check if the object is composed of other BaseObjects.
`keys`()	Return a list of available sets.
`load`(*args)	Load the dataset.
`load_from_path`(serial)	Load object from file location.
`load_from_serial`(serial)	Load object from serialized memory container.
`loader_func`([return_X_y, return_type])	Load ItalyPowerDemand time series classification problem.
`reset`()	Reset the object to a clean post-init state.
`save`([path, serialization_format])	Save serialized self to bytes-like object or to (.zip) file.
`set_config`(**config_dict)	Set config flags to given values.
`set_params`(**params)	Set the parameters of this object.
`set_random_state`([random_state, deep, ...])	Set random_state pseudo-random seed parameters for self.
`set_tags`(**tag_dict)	Set instance level tag overrides to given values.

get_loader_func