Repeat

Repeat

class Repeat(splitter, times=1, mode='entry', random_repeat=False)[source]

Add repetitions to a splitter, element-wise or sequence-wise.

Element-wise means: if the original splitter splits a series s into s1, s2, s3, then a 2-times repeat splits s into s1, s1, s2, s2, s3, s3. Sequence-wise means: if the original splitter splits a series s into s1, s2, s3, then a 2-times repeat splits s into s1, s2, s3, s1, s2, s3.

This splitter also allows to control whether repetitions are exact or independent pseuo-random, for stochastic splitters.

Parameters:

splittersktime splitter object, BaseSplitter descendant instance

splitter to repeat

timesint, default=1

number of times to repeat the splitter

modestr, one of “entry” and “sequence”, default=”entry”

mode of repetition “entry” repeats each entry of the split times times “sequence” repeats the entire sequence of splits times times

random_repeatbool, default=False

whether repetitions should be exact or independent pseudo-random If False, repetitions are exact (default) If True, repetitions are random, splitter is cloned for each repetition. Note: if a random seed is set in splitter, the effect is the same as setting random_repeat to False, even if random_repeat is True.

Methods

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_cutoffs([y])	Return the cutoff points in .iloc[] context.
get_fh()	Return the forecasting horizon.
get_n_splits(y)	Return the number of splits.
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 splitter.
is_composite()	Check if the object is composed of other BaseObjects.
load_from_path(serial)	Load object from file location.
load_from_serial(serial)	Load object from serialized memory container.
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.
split(y)	Get iloc references to train/test splits of y.
split_loc(y)	Get loc references to train/test splits of y.
split_series(y)	Split y into training and test windows.