# skfolio.uncertainty_set.BaseCovarianceUncertaintySet ### *class* skfolio.uncertainty_set.BaseCovarianceUncertaintySet(prior_estimator=None) Base class for all Covariance Uncertainty Set estimators in `skfolio`. ### Methods | [`fit`](#skfolio.uncertainty_set.BaseCovarianceUncertaintySet.fit)(X[, y]) | Fit the Covariance Uncertainty set estimator. | |-------------------------------------------------------------------------|-------------------------------------------------| | [`get_metadata_routing`](#skfolio.uncertainty_set.BaseCovarianceUncertaintySet.get_metadata_routing)() | Get metadata routing for this estimator. | | [`get_params`](#skfolio.uncertainty_set.BaseCovarianceUncertaintySet.get_params)([deep]) | Get parameters for this estimator. | | [`set_params`](#skfolio.uncertainty_set.BaseCovarianceUncertaintySet.set_params)(\*\*params) | Set the parameters of this estimator. | ### Notes All estimators should specify all the parameters that can be set at the class level in their `__init__` as explicit keyword arguments (no `*args` or `**kwargs`). #### *abstractmethod* fit(X, y=None, \*\*fit_params) Fit the Covariance Uncertainty set estimator. * **Parameters:** **X** *array-like of shape (n_observations, n_assets)* : Price returns of the assets. **y** *array-like of shape (n_observations, n_factors), optional* : Price returns of factors. The default is `None`. **\*\*fit_params** *dict* : Parameters to pass to the underlying estimators. Only available if `enable_metadata_routing=True`, which can be set by using `sklearn.set_config(enable_metadata_routing=True)`. See [Metadata Routing User Guide](https://skfolio.org/user_guide/metadata_routing.html.md#metadata-routing) for more details. * **Returns:** **self** *BaseCovarianceUncertaintySet* : Fitted estimator. #### get_metadata_routing() Get metadata routing for this estimator. Routes metadata passed to `fit` to the `fit` method of `prior_estimator`. * **Returns:** **routing** *MetadataRouter* : Metadata routing configuration. #### get_params(deep=True) Get parameters for this estimator. * **Parameters:** **deep** *bool, default=True* : If True, will return the parameters for this estimator and contained subobjects that are estimators. * **Returns:** **params** *dict* : Parameter names mapped to their values. #### set_params(\*\*params) Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as `Pipeline`). The latter have parameters of the form `__` so that it’s possible to update each component of a nested object. * **Parameters:** **\*\*params** *dict* : Estimator parameters. * **Returns:** **self** *estimator instance* : Estimator instance.