code: def test_fit_base_estimators_false():
      np.random.seed(123)
      clf1 = LogisticRegression(solver="liblinear", multi_class="ovr")
      clf2 = RandomForestClassifier(n_estimators=10)
      clf3 = GaussianNB()
  
      clf1.fit(X, y)
      clf2.fit(X, y)
      clf3.fit(X, y)
  
      eclf = EnsembleVoteClassifier(
          clfs=[clf1, clf2, clf3],
          voting="hard",
          fit_base_estimators=False,
      )
  
      eclf.fit(X, y)
      assert round(eclf.score(X, y), 2) == 0.97
  
imports: import random
  import numpy
  import pytest
  from packaging.version import Version
  from sklearn import __version__
  from sklearn import exceptions
  from sklearn.base import clone
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import GridSearchCV, cross_val_score
  from sklearn.naive_bayes import GaussianNB
  from sklearn.neighbors import KNeighborsClassifier
  from mlxtend.classifier import EnsembleVoteClassifier
  from mlxtend.data import iris_data
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 2 for calling a global function with example usage: test_fit_base_estimators_false() without return types