code: def test_base_chain_fit_and_predict(response_method):
      # Fit base chain and verify predict performance
      X, Y = generate_multilabel_dataset_with_correlations()
      chains = [
          RegressorChain(Ridge()),
          ClassifierChain(LogisticRegression()),
      ]
      for chain in chains:
          chain.fit(X, Y)
          Y_pred = chain.predict(X)
          assert Y_pred.shape == Y.shape
          assert [c.coef_.size for c in chain.estimators_] == list(
              range(X.shape[1], X.shape[1] + Y.shape[1])
          )
  
      Y_prob = getattr(chains[1], response_method)(X)
      if response_method == "predict_log_proba":
          Y_prob = np.exp(Y_prob)
      Y_binary = Y_prob >= 0.5
      assert_array_equal(Y_binary, Y_pred)
  
      assert isinstance(chains[1], ClassifierMixin)
  
imports: import re
  import numpy
  import pytest
  from joblib import cpu_count
  from sklearn import datasets
  from sklearn.base import ClassifierMixin, clone
  from sklearn.datasets import load_linnerud, make_classification, make_multilabel_classification, make_regression
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.ensemble import GradientBoostingRegressor, RandomForestClassifier, StackingRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import Lasso, LinearRegression, LogisticRegression, OrthogonalMatchingPursuit, PassiveAggressiveClassifier, Ridge, SGDClassifier, SGDRegressor
  from sklearn.metrics import jaccard_score, mean_squared_error
  from sklearn.model_selection import GridSearchCV, train_test_split
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.multioutput import ClassifierChain, MultiOutputClassifier, MultiOutputRegressor, RegressorChain
  from sklearn.pipeline import make_pipeline
  from sklearn.svm import LinearSVC
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.utils import shuffle
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import BSR_CONTAINERS, COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 25 for calling a global function with example usage: test_base_chain_fit_and_predict(response_method) without return types