code: def test_clone_params_pass():
      iris = load_iris()
      X = iris.data
      y = iris.target
      lr = SoftmaxRegression(random_seed=1)
      efs1 = EFS(
          lr,
          min_features=2,
          max_features=2,
          scoring="accuracy",
          cv=0,
          clone_estimator=False,
          print_progress=False,
          n_jobs=1,
      )
      efs1 = efs1.fit(X, y)
      assert efs1.best_idx_ == (1, 3)
  
imports: import numpy
  import pandas
  from numpy.testing import assert_almost_equal
  from packaging.version import Version
  from sklearn import __version__
  from sklearn.datasets import load_iris
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import GroupKFold
  from sklearn.neighbors import KNeighborsClassifier
  from mlxtend.classifier import SoftmaxRegression
  from mlxtend.data import boston_housing_data
  from mlxtend.feature_selection import ExhaustiveFeatureSelector
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 11 for calling a global function with example usage: test_clone_params_pass() without return types