code: def test_multiclass_relevant_features_selected(self):
      y0 = np.zeros(100)
      y1 = np.repeat(1, 100)
      y2 = np.repeat(2, 100)
      y_multi = pd.Series(np.uint8(np.concatenate([y0, y1, y2])))
      X_multi = pd.DataFrame()
      X_multi["irrelevant"] = np.concatenate(
          [np.zeros(298), np.array([0.01, -0.01])]
      )
      X_multi["relevant"] = X_multi["irrelevant"].copy()
      X_multi["relevant"][y_multi == 0] = np.random.uniform(2, 3, 100)
  
      selector = FeatureSelector(
          multiclass=True, n_significant=3, ml_task="classification"
      )
  
      selector.fit(X_multi, y_multi)
  
      self.assertEqual(selector.relevant_features, ["relevant"])
  
file_path: tsfresh/tests/units/transformers/test_feature_selector.py
imports: from builtins import range
  from unittest import TestCase
  import numpy
  import pandas
  from tsfresh.transformers.feature_selector import FeatureSelector
label_desc: Use image node_id 8 for calling the FeatureSelectorTestCase obj's underlying member method code with example usage: obj.test_multiclass_relevant_features_selected() without return types