ACSF1

ACSF1

class ACSF1(return_mtype='pd-multiindex')[source]

ACSF1 time series classification problem.

Example of a univariate classification dataset with long idle periods.

Notes

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

Examples

>>> from sktime.datasets.classification import ACSF1
>>> X, y = ACSF1().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 dataset on power consumption of typical appliances.
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