code: def test_cohort_filter_excludes(self):
      (
          X_train,
          X_test,
          y_train,
          y_test,
          numeric,
          categorical,
      ) = create_simple_titanic_data()
      feature_names = categorical + numeric
      clf = create_titanic_pipeline(X_train, y_train)
      categorical_features = categorical
      # the indexes other than 0, 2 correspond to Q
      filters = [
          {
              ARG: [0, 2],
              COLUMN: EMBARKED,
              METHOD: CohortFilterMethods.METHOD_EXCLUDES,
          }
      ]
      validation_data = create_validation_data(X_test, y_test)
      filter_embarked = X_test[EMBARKED].isin(["Q"])
      validation_data = validation_data.loc[filter_embarked]
      model_task = ModelTask.CLASSIFICATION
      run_rai_insights(
          validation_data,
          clf,
          X_train,
          y_train,
          X_test,
          y_test,
          feature_names,
          categorical_features,
          model_task,
          filters=filters,
      )
  
imports: import numpy
  import pandas
  import pytest
  from tests.common_utils import create_iris_data
  from erroranalysis._internal.constants import ARG, COLUMN, METHOD, PRED_Y, ROW_INDEX, TRUE_Y
  from rai_test_utils.datasets.tabular import create_housing_data, create_simple_titanic_data
  from rai_test_utils.models.sklearn import create_sklearn_random_forest_regressor, create_sklearn_svm_classifier, create_titanic_pipeline
  from raiutils.cohort import CohortFilterMethods
  from raiutils.models import ModelTask
  from responsibleai.rai_insights import RAIInsights
label_desc: Use image node_id 10 for calling the TestCohortFilterRAIInsights obj's underlying member method code with example usage: obj.test_cohort_filter_excludes() without return types