GunPoint

GunPoint

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

GunPoint time series classification problem.

Example of a univariate problem with equal-length series.

Notes

Dimensionality: univariate Series length: 150 Train cases: 50 Test cases: 150 Number of classes: 2

This dataset involves one female actor and one male actor making a motion with their hand. The two classes are: Gun-Draw and Point. For Gun-Draw, the actors have their hands by their sides. They draw a replicate gun from a hip-mounted holster, point it at a target for approximately one second, then return the gun to the holster, and their hands to their sides. For Point, the actors have their hands by their sides. They point with their index fingers to a target for approximately one second, and then return their hands to their sides. For both classes, we tracked the centroid of the actor’s right hands in both X- and Y-axes, which appear to be highly correlated. The data in the archive is just the X-axis.

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

Examples

>>> from sktime.datasets.classification import GunPoint
>>> X, y = GunPoint().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 the GunPoint time series classification problem and returns X and y.
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