code: def expected_feature_balance_measures_gender():
      # Note: Compared to SynapseML, this module does not compute n_pmi_y,
      # n_pmi_xy, and s_pmi. However, this module does compute TTest and
      # TTestPValue so their actual values are used.
      return {
          "ClassA": "Male",
          "ClassB": "Female",
          "FeatureName": "Gender",
          "StatisticalParity": 0.16666666666666669,
          "PointwiseMutualInfo": 0.4054651081081645,
          "SorensonDiceCoeff": 0.1190476190476191,
          "JaccardIndex": 0.20000000000000004,
          "KendallRankCorrelation": 0.18801108758923135,
          "LogLikelihoodRatio": 0.6931471805599454,
          "TTest": -0.1855414423,
          "TTestPValue": 0.4349585786,
      }
  
file_path: responsible-ai-toolbox/responsibleai/tests/databalanceanalysis/conftest.py
imports: import pandas
  import pytest
  from tests.common_utils import create_adult_income_dataset
label_desc: Use image node_id 10 for calling a global function with example usage: expected_feature_balance_measures_gender() and returns: dict