Airline

Airline

class Airline[source]

Load the airline univariate time series dataset [1].

Notes

The classic Box & Jenkins airline data. Monthly totals of international airline passengers, 1949 to 1960.

Dimensionality: univariate Series length: 144 Frequency: Monthly Number of cases: 1

This data shows an increasing trend, non-constant (increasing) variance and periodic, seasonal patterns.

References

[1]

Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (1976) Time Series Analysis, Forecasting and Control. Third Edition. Holden-Day. Series G.

Examples

>>> from sktime.datasets.forecasting import Airline
>>> dataset = Airline()
>>> y = dataset.load("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()	Load the airline univariate time series dataset [1].
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