code: def test_string_scoring_clf():
      iris = load_iris()
      X = iris.data
      y = iris.target
      knn = KNeighborsClassifier(n_neighbors=4)
      sfs1 = SFS(knn, k_features=3, cv=0)
      sfs1 = sfs1.fit(X, y)
  
      sfs2 = SFS(knn, k_features=3, scoring="accuracy", cv=0)
      sfs2 = sfs2.fit(X, y)
  
      sfs3 = SFS(
          knn, k_features=3, scoring=make_scorer(accuracy_score), cv=0
      )
      sfs3 = sfs2.fit(X, y)
  
      assert sfs1.k_score_ == sfs2.k_score_
      assert sfs1.k_score_ == sfs3.k_score_
  
imports: import numpy
  import pandas
  from numpy import nan
  from numpy.testing import assert_almost_equal
  from packaging.version import Version
  from sklearn import __version__
  from sklearn.datasets import load_iris
  from sklearn.decomposition import PCA
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LinearRegression
  from sklearn.metrics import accuracy_score, make_scorer, roc_auc_score
  from sklearn.model_selection import GridSearchCV, GroupKFold
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.pipeline import Pipeline
  from mlxtend.classifier import SoftmaxRegression
  from mlxtend.data import boston_housing_data
  from mlxtend.feature_selection import SequentialFeatureSelector
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 35 for calling a global function with example usage: test_string_scoring_clf() without return types