yobx.sklearn.model_selection.random_search

yobx.sklearn.model_selection.random_search.sklearn_randomized_search_cv(g: GraphBuilderExtendedProtocol, sts: Dict, outputs: List[str], estimator: RandomizedSearchCV, X: str, name: str = 'randomized_search_cv') → str | Tuple[str, ...]

Converts a sklearn.model_selection.RandomizedSearchCV into ONNX by delegating to the converter registered for best_estimator_.

After fitting, RandomizedSearchCV exposes the best model found during the randomized cross-validated search via its best_estimator_ attribute. The ONNX graph produced here is therefore identical to converting that best estimator directly.

X ──[best_estimator_ converter]──► output(s)

Parameters:

• g – the graph builder to add nodes to

• sts – shapes and types defined by scikit-learn

• outputs – desired output tensor names for the result

• estimator – a fitted RandomizedSearchCV

• X – name of the input tensor

• name – prefix used for names of nodes added by this converter

Returns:

name of the output tensor, or a tuple of output tensor names

Raises:

AttributeError – if estimator has not been fitted yet (i.e. best_estimator_ does not exist)