code: def _parse_sklearn_model_selection(topology, model, inputs):
      """
      :param topology: Topology object
      :param model: A *sklearn.model_selection* object
      :param inputs: A list of Variable objects
      :return: Output produced by sklearn.model_selection.* object
      """
      op = model.best_estimator_
      var_output = _parse_sklearn_api(topology, op, inputs)
      return var_output
  
imports: from collections import OrderedDict
  from copy import deepcopy
  import pprint
  from uuid import uuid4
  import numpy
  from onnxconverter_common.optimizer import LinkedNode, _topological_sort
  from sklearn import pipeline
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import BaggingClassifier, BaggingRegressor
  from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
  from sklearn.multioutput import MultiOutputRegressor, RegressorChain
  from sklearn.preprocessing import OneHotEncoder
  from .containers import CommonSklearnModelContainer, CommonONNXModelContainer, CommonSparkMLModelContainer
  from ._topology import Topology
  from ._utils import sklearn_installed, sparkml_installed
  from .operator_converters import constants
  from .supported import get_sklearn_api_operator_name, get_onnxml_api_operator_name, get_sparkml_api_operator_name
label_desc: Use image node_id 13 for calling a global function with example usage: _parse_sklearn_model_selection(topology, model, inputs) and returns: var_output