skbase.base.BaseMetaEstimator

class skbase.base.BaseMetaEstimator

Parameter and tag management for estimators composed of named objects.

Allows estimators to get and set nested parameters when a parameter of the the class has values that follow the named object specification. For example, in a pipeline class with the the “step” parameter accepting named objects, this would allow get_params and set_params to retrieve and update the parameters of the objects in each step.

Note: if inheriting from an abstract descendant of BaseEstimator, use BaseMetaEstimatorMixin and not BaseMetaEstimator.

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.
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 skbase object.
is_composite()	Check if the object is composite.
reset()	Reset the object to a clean post-init state.
set_config(**config_dict)	Set config flags to given values.
set_params(**kwargs)	Set the object's direct parameters and the parameters of components.
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.

See also

BaseMetaEstimatorMixin

Mixin for inheriting from abstract descendants of BaseObject. Same as BaseMetaObject, but does not inherit from BaseObject.

BaseMetaObject

Provides similar functionality to BaseMetaEstimator, but does not have the estimator interface for fitting and fitted parameters.

check_is_fitted(method_name=None)

Check if the estimator has been fitted.

Check if _is_fitted attribute is present and True. The is_fitted attribute should be set to True in calls to an object’s fit method.

If not, raises a NotFittedError.

Parameters:

method_namestr, optional

Name of the method that called this function. If provided, the error message will include this information.

Raises:

NotFittedError

If the estimator has not been fitted yet.

clone()

Obtain a clone of the object with same hyper-parameters and config.

A clone is a different object without shared references, in post-init state. This function is equivalent to returning sklearn.clone of self.

Equivalent to constructing a new instance of type(self), with parameters of self, that is, type(self)(**self.get_params(deep=False)).

If configs were set on self, the clone will also have the same configs as the original, equivalent to calling cloned_self.set_config(**self.get_config()).

Also equivalent in value to a call of self.reset, with the exception that clone returns a new object, instead of mutating self like reset.

Raises:

RuntimeError if the clone is non-conforming, due to faulty __init__.

clone_tags(estimator, tag_names=None)

Clone tags from another object as dynamic override.

Every scikit-base compatible object has a dictionary of tags. Tags may be used to store metadata about the object, or to control behaviour of the object.

Tags are key-value pairs specific to an instance self, they are static flags that are not changed after construction of the object.

clone_tags sets dynamic tag overrides from another object, estimator.

The clone_tags method should be called only in the __init__ method of an object, during construction, or directly after construction via __init__.

The dynamic tags are set to the values of the tags in estimator, with the names specified in tag_names.

The default of tag_names writes all tags from estimator to self.

Current tag values can be inspected by get_tags or get_tag.

Parameters:

estimatorAn instance of :class:BaseObject or derived class

tag_namesstr or list of str, default = None

Names of tags to clone. The default (None) clones all tags from estimator.

Returns:

self

Reference to self.

classmethod create_test_instance(parameter_set='default')

Construct an instance of the class, using first test parameter set.

Parameters:

parameter_setstr, default=”default”

Name of the set of test parameters to return, for use in tests. If no special parameters are defined for a value, will return “default” set.

Returns:

instanceinstance of the class with default parameters

classmethod create_test_instances_and_names(parameter_set='default')

Create list of all test instances and a list of names for them.

Parameters:

parameter_setstr, default=”default”

Name of the set of test parameters to return, for use in tests. If no special parameters are defined for a value, will return “default” set.

Returns:

objslist of instances of cls

i-th instance is cls(**cls.get_test_params()[i])

nameslist of str, same length as objs

i-th element is name of i-th instance of obj in tests. The naming convention is {cls.__name__}-{i} if more than one instance, otherwise {cls.__name__}

classmethod get_class_tag(tag_name, tag_value_default=None)

Get class tag value from class, with tag level inheritance from parents.

Every scikit-base compatible object has a dictionary of tags. Tags may be used to store metadata about the object, or to control behaviour of the object.

Tags are key-value pairs specific to an instance self, they are static flags that are not changed after construction of the object.

The get_class_tag method is a class method, and retrieves the value of a tag taking into account only class-level tag values and overrides.

It returns the value of the tag with name tag_name from the object, taking into account tag overrides, in the following order of descending priority:

1. Tags set in the _tags attribute of the class.

2. Tags set in the _tags attribute of parent classes,

in order of inheritance.

Does not take into account dynamic tag overrides on instances, set via set_tags or clone_tags, that are defined on instances.

To retrieve tag values with potential instance overrides, use the get_tag method instead.

Parameters:

tag_namestr

Name of tag value.

tag_value_defaultany type

Default/fallback value if tag is not found.

Returns:

tag_value

Value of the tag_name tag in self. If not found, returns tag_value_default.

classmethod get_class_tags()

Get class tags from class, with tag level inheritance from parent classes.

Every scikit-base compatible object has a dictionary of tags. Tags may be used to store metadata about the object, or to control behaviour of the object.

Tags are key-value pairs specific to an instance self, they are static flags that are not changed after construction of the object.

The get_class_tags method is a class method, and retrieves the value of a tag taking into account only class-level tag values and overrides.

It returns a dictionary with keys being keys of any attribute of _tags set in the class or any of its parent classes.

Values are the corresponding tag values, with overrides in the following order of descending priority:

1. Tags set in the _tags attribute of the class.

2. Tags set in the _tags attribute of parent classes,

in order of inheritance.

Instances can override these tags depending on hyper-parameters.

To retrieve tags with potential instance overrides, use the get_tags method instead.

Does not take into account dynamic tag overrides on instances, set via set_tags or clone_tags, that are defined on instances.

For including overrides from dynamic tags, use get_tags.

Returns:

collected_tagsdict

Dictionary of tag name : tag value pairs. Collected from _tags class attribute via nested inheritance. NOT overridden by dynamic tags set by set_tags or clone_tags.

get_config()

Get config flags for self.

Configs are key-value pairs of self, typically used as transient flags for controlling behaviour.

get_config returns dynamic configs, which override the default configs.

Default configs are set in the class attribute _config of the class or its parent classes, and are overridden by dynamic configs set via set_config.

Configs are retained under clone or reset calls.

Returns:

config_dictdict

Dictionary of config name : config value pairs. Collected from _config class attribute via nested inheritance and then any overrides and new tags from _onfig_dynamic object attribute.

get_fitted_params(deep=True)

Get fitted parameters.

State required:

Requires state to be “fitted”.

Parameters:

deepbool, default=True

Whether to return fitted parameters of components.

• If True, will return a dict of parameter name : value for this object, including fitted parameters of fittable components (= BaseEstimator-valued parameters).

• If False, will return a dict of parameter name : value for this object, but not include fitted parameters of components.

Returns:

fitted_paramsdict with str-valued keys

Dictionary of fitted parameters, paramname : paramvalue keys-value pairs include:

• always: all fitted parameters of this object, as via get_param_names values are fitted parameter value for that key, of this object

• if deep=True, also contains keys/value pairs of component parameters parameters of components are indexed as [componentname]__[paramname] all parameters of componentname appear as paramname with its value

• if deep=True, also contains arbitrary levels of component recursion, e.g., [componentname]__[componentcomponentname]__[paramname], etc

classmethod get_param_defaults()

Get object’s parameter defaults.

Returns:

default_dict: dict[str, Any]

Keys are all parameters of cls that have a default defined in __init__. Values are the defaults, as defined in __init__.

classmethod get_param_names(sort=True)

Get object’s parameter names.

Parameters:

sortbool, default=True

Whether to return the parameter names sorted in alphabetical order (True), or in the order they appear in the class __init__ (False).

Returns:

param_names: list[str]

List of parameter names of cls. If sort=False, in same order as they appear in the class __init__. If sort=True, alphabetically ordered.

get_params(deep=True)

Get a dict of parameters values for this object.

This expands on get_params of standard BaseObject by also retrieving components parameters when deep=True a component’s follows the named object API (either sequence of str, BaseObject tuples or dict[str, BaseObject]).

Parameters:

deepbool, default=True

Whether to return parameters of components.

• If True, will return a dict of parameter name : value for this object, including parameters of components.

• If False, will return a dict of parameter name : value for this object, but not include parameters of components.

Returns:

dict[str, Any]

Dictionary of parameter name and value pairs. Includes direct parameters and indirect parameters whose values implement get_params or follow the named object API (either sequence of str, BaseObject tuples or dict[str, BaseObject]).

• If deep=False the name-value pairs for this object’s direct parameters (you can see these via get_param_names) are returned.

• If deep=True then the parameter name-value pairs are returned for direct and component (indirect) parameters.

  • When a BaseObject’s direct parameter value implements get_params the component parameters are returned as [direct_param_name]__[component_param_name] for 1st level components. Arbitrary levels of component recursion are supported (if the component has parameter’s whose values are objects that implement get_params). In this case, return parameters follow [direct_param_name]__[component_param_name]__[param_name] format.

  • When a BaseObject’s direct parameter value is a sequence of (name, BaseObject) tuples or dict[str, BaseObject] the parameters name and value pairs of all component objects are returned. The parameter naming follows scikit-learn convention of treating named component objects like they are direct parameters; therefore, the names are assigned as [component_param_name]__[param_name].

get_tag(tag_name, tag_value_default=None, raise_error=True)

Get tag value from instance, with tag level inheritance and overrides.

Every scikit-base compatible object has a dictionary of tags. Tags may be used to store metadata about the object, or to control behaviour of the object.

Tags are key-value pairs specific to an instance self, they are static flags that are not changed after construction of the object.

The get_tag method retrieves the value of a single tag with name tag_name from the instance, taking into account tag overrides, in the following order of descending priority:

1. Tags set via set_tags or clone_tags on the instance,

at construction of the instance.

2. Tags set in the _tags attribute of the class.

3. Tags set in the _tags attribute of parent classes,

in order of inheritance.

Parameters:

tag_namestr

Name of tag to be retrieved

tag_value_defaultany type, optional; default=None

Default/fallback value if tag is not found

raise_errorbool

whether a ValueError is raised when the tag is not found

Returns:

tag_valueAny

Value of the tag_name tag in self. If not found, raises an error if raise_error is True, otherwise it returns tag_value_default.

Raises:

ValueError, if raise_error is True.

The ValueError is then raised if tag_name is not in self.get_tags().keys().

get_tags()

Get tags from instance, with tag level inheritance and overrides.

Every scikit-base compatible object has a dictionary of tags. Tags may be used to store metadata about the object, or to control behaviour of the object.

Tags are key-value pairs specific to an instance self, they are static flags that are not changed after construction of the object.

The get_tags method returns a dictionary of tags, with keys being keys of any attribute of _tags set in the class or any of its parent classes, or tags set via set_tags or clone_tags.

Values are the corresponding tag values, with overrides in the following order of descending priority:

1. Tags set via set_tags or clone_tags on the instance,

at construction of the instance.

2. Tags set in the _tags attribute of the class.

3. Tags set in the _tags attribute of parent classes,

in order of inheritance.

Returns:

collected_tagsdict

Dictionary of tag name : tag value pairs. Collected from _tags class attribute via nested inheritance and then any overrides and new tags from _tags_dynamic object attribute.

classmethod get_test_params(parameter_set='default')

Return testing parameter settings for the skbase object.

get_test_params is a unified interface point to store parameter settings for testing purposes. This function is also used in create_test_instance and create_test_instances_and_names to construct test instances.

get_test_params should return a single dict, or a list of dict.

Each dict is a parameter configuration for testing, and can be used to construct an “interesting” test instance. A call to cls(**params) should be valid for all dictionaries params in the return of get_test_params.

The get_test_params need not return fixed lists of dictionaries, it can also return dynamic or stochastic parameter settings.

Parameters:

parameter_setstr, default=”default”

Name of the set of test parameters to return, for use in tests. If no special parameters are defined for a value, will return “default” set.

Returns:

paramsdict or list of dict, default = {}

Parameters to create testing instances of the class Each dict are parameters to construct an “interesting” test instance, i.e., MyClass(**params) or MyClass(**params[i]) creates a valid test instance. create_test_instance uses the first (or only) dictionary in params

is_composite()

Check if the object is composite.

A composite object is an object which contains objects as parameter values.

Returns:

bool

Whether self contains a parameter whose value is a BaseObject, list of (str, BaseObject) tuples or dict[str, BaseObject].

property is_fitted

Whether fit has been called.

Inspects object’s _is_fitted` attribute that should initialize to ``False during object construction, and be set to True in calls to an object’s fit method.

Returns:

bool

Whether the estimator has been fit.

reset()

Reset the object to a clean post-init state.

Results in setting self to the state it had directly after the constructor call, with the same hyper-parameters. Config values set by set_config are also retained.

A reset call deletes any object attributes, except:

• hyper-parameters = arguments of __init__ written to self, e.g., self.paramname where paramname is an argument of __init__

• object attributes containing double-underscores, i.e., the string “__”. For instance, an attribute named “__myattr” is retained.

• config attributes, configs are retained without change. That is, results of get_config before and after reset are equal.

Class and object methods, and class attributes are also unaffected.

Equivalent to clone, with the exception that reset mutates self instead of returning a new object.

After a self.reset() call, self is equal in value and state, to the object obtained after a constructor call``type(self)(**self.get_params(deep=False))``.

Returns:

self

Instance of class reset to a clean post-init state but retaining the current hyper-parameter values.

set_config(**config_dict)

Set config flags to given values.

Configs are key-value pairs of self, typically used as transient flags for controlling behaviour.

set_config sets dynamic configs, which override the default configs.

Default configs are set in the class attribute _config of the class or its parent classes, and are overridden by dynamic configs set via set_config.

Configs are retained under clone or reset calls.

Parameters:

config_dictdict

Dictionary of config name : config value pairs.

Returns:

selfreference to self.

Notes

Changes object state, copies configs in config_dict to self._config_dynamic.

set_params(**kwargs)

Set the object’s direct parameters and the parameters of components.

Valid parameter keys can be listed with get_params().

Like BaseObject implementation it allows values of indirect parameters of a component to be set when a parameter’s value is an object that implements set_params. This also also expands the functionality to allow parameter to allow the indirect parameters of components to be set when a parameter’s values follow the named object API (either sequence of str, BaseObject tuples or dict[str, BaseObject]).

Returns:

Self

Instance of self.

set_random_state(random_state=None, deep=True, self_policy='copy')

Set random_state pseudo-random seed parameters for self.

Finds random_state named parameters via self.get_params, and sets them to integers derived from random_state via set_params. These integers are sampled from chain hashing via sample_dependent_seed, and guarantee pseudo-random independence of seeded random generators.

Applies to random_state parameters in self, depending on self_policy, and remaining component objects if and only if deep=True.

Note: calls set_params even if self does not have a random_state, or none of the components have a random_state parameter. Therefore, set_random_state will reset any scikit-base object, even those without a random_state parameter.

Parameters:

random_stateint, RandomState instance or None, default=None

Pseudo-random number generator to control the generation of the random integers. Pass int for reproducible output across multiple function calls.

deepbool, default=True

Whether to set the random state in skbase object valued parameters, i.e., component estimators.

• If False, will set only self’s random_state parameter, if exists.

• If True, will set random_state parameters in component objects as well.

self_policystr, one of {“copy”, “keep”, “new”}, default=”copy”

• “copy” : self.random_state is set to input random_state

• “keep” : self.random_state is kept as is

• “new” : self.random_state is set to a new random state,

derived from input random_state, and in general different from it

Returns:

selfreference to self

set_tags(**tag_dict)

Set instance level tag overrides to given values.

Every scikit-base compatible object has a dictionary of tags. Tags may be used to store metadata about the object, or to control behaviour of the object.

Tags are key-value pairs specific to an instance self, they are static flags that are not changed after construction of the object.

set_tags sets dynamic tag overrides to the values as specified in tag_dict, with keys being the tag name, and dict values being the value to set the tag to.

The set_tags method should be called only in the __init__ method of an object, during construction, or directly after construction via __init__.

Current tag values can be inspected by get_tags or get_tag.

Parameters:

**tag_dictdict

Dictionary of tag name: tag value pairs.

Returns:

Self

Reference to self.