code: def test_performances():
      X, y = make_blobs(n_samples=1000, random_state=0, centers=2)
  
      # make labels imbalanced by remove all but 100 instances from class 1
      indexes = np.ones(X.shape[0]).astype(bool)
      ind = np.array([False] * 100 + list(((y == 1)[100:])))
      indexes[ind] = 0
      X = X[indexes]
      y = y[indexes]
      n_samples, n_features = X.shape
  
      clf = SkopeRulesClassifier()
      # fit
      clf.fit(X, y)
      # with lists
      clf.fit(X.tolist(), y.tolist())
      y_pred = clf.predict(X)
      assert y_pred.shape == (n_samples,)
      # training set performance
      assert accuracy_score(y, y_pred) > 0.83
  
file_path: imodels/tests/skope_rules_test.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_equal, assert_no_warnings, assert_raises, suppress_warnings, assert_warns
  from sklearn.datasets import load_iris, make_blobs
  from sklearn.metrics import accuracy_score
  from sklearn.model_selection import ParameterGrid
  from sklearn.utils import check_random_state
  from imodels.rule_set.skope_rules import SkopeRulesClassifier
label_desc: Use image node_id 6 for calling a global function with example usage: test_performances() without return types