code: def test_classifier_refit():
      # Classifier can be retrained on different labels and features.
      clf = PassiveAggressiveClassifier(max_iter=5).fit(X, y)
      assert_array_equal(clf.classes_, np.unique(y))
  
      clf.fit(X[:, :-1], iris.target_names[y])
      assert_array_equal(clf.classes_, iris.target_names)
  
imports: import numpy
  import pytest
  from sklearn.base import ClassifierMixin
  from sklearn.datasets import load_iris
  from sklearn.linear_model import PassiveAggressiveClassifier, PassiveAggressiveRegressor
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 3 for calling a global function with example usage: test_classifier_refit() without return types