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EvoForestTSWM

EvoForestTSWM

class EvoForestTSWM(pooling='full')[source]

EvoForest Time-Series World-Model encoder (TS-WM).

A frozen, closed-form feature transform; see the module docstring. No learned weights; fit is empty. A peer of Catch22 / MiniRocket.

Parameters:
pooling{“full”, “pruned”}, default=”full”

423 features (“full”) or 245 (“pruned”).

Attributes:
is_fitted

Whether fit has been called.

Methods

check_is_fitted([method_name])

Check if the estimator has been fitted.

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.

fit(X[, y])

Fit transformer to X, optionally to y.

fit_transform(X[, y])

Fit to data, then transform it.

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_fitted_params([deep])

Get fitted parameters.

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 estimator.

inverse_transform(X[, y])

Inverse transform X and return an inverse transformed version.

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.

transform(X[, y])

Transform X and return a transformed version.

update(X[, y, update_params])

Update transformer with X, optionally y.