class_docstr: Test cases for the whole feature selection algorithm.
class_docstr_tok: ["Test","cases","for","the","whole","feature","selection","algorithm","."]
code: def test_all_features_bad(self):
      # Mixed case with real target
      y = pd.Series(np.random.normal(0, 1, 1000))
      X = pd.DataFrame(index=range(1000))
  
      X["irr1"] = np.random.binomial(0, 0.1, 1000)
      X["irr2"] = np.random.binomial(0, 0.15, 1000)
      X["irr3"] = np.random.binomial(0, 0.05, 1000)
      X["irr4"] = np.random.binomial(0, 0.2, 1000)
      X["irr5"] = np.random.binomial(0, 0.25, 1000)
      X["irr6"] = np.random.binomial(0, 0.01, 1000)
  
      df_bh = calculate_relevance_table(X, y)
      feat_rej = df_bh.loc[df_bh.relevant].feature
  
      self.assertEqual(len(feat_rej), 0)
  
file_path: tsfresh/tests/units/feature_selection/test_feature_significance.py
imports: from unittest import TestCase
  import numpy
  import pandas
  from tsfresh.feature_selection.relevance import calculate_relevance_table
label_desc: Use image node_id 8 for calling the FeatureSignificanceTestCase obj's underlying member method code with example usage: obj.test_all_features_bad() without return types