code: def test_matrix_filter_adult_census_quantile_binning(
      self, string_labels, metric
  ):
      (
          X_train,
          X_test,
          y_train,
          y_test,
          categorical_features,
      ) = create_adult_census_data(string_labels)
  
      model_task = ModelTask.CLASSIFICATION
      feature_names = X_test.columns.tolist()
      matrix_features = ["Capital Gain"]
      # validate quantile binning for column with many zero values
      model = create_kneighbors_classifier(X_train, y_train)
  
      # validate warning printed
      err_capg = (
          "Removing duplicate bin edges for quantile binning of "
          "feature Capital Gain. There are too many duplicate "
          "values for the specified number of bins."
      )
      with pytest.warns(UserWarning, match=err_capg):
          run_error_analyzer(
              model,
              X_test,
              y_test,
              feature_names,
              categorical_features,
              model_task=model_task,
              matrix_features=matrix_features,
              quantile_binning=True,
              metric=metric,
          )
      matrix_features = ["Capital Gain", "Capital Loss"]
      err_capl = (
          "Removing duplicate bin edges for quantile binning of "
          "feature Capital Loss. There are too many duplicate "
          "values for the specified number of bins."
      )
      with pytest.warns(UserWarning) as warninfo:
          run_error_analyzer(
              model,
              X_test,
              y_test,
              feature_names,
              categorical_features,
              model_task=model_task,
              matrix_features=matrix_features,
              quantile_binning=True,
              metric=metric,
          )
      warns = {
          (warn.category, warn.message.args[0]) for warn in warninfo
      }
      expected = {(UserWarning, err_capg), (UserWarning, err_capl)}
      for expected_warning in expected:
          assert expected_warning in warns
  
imports: import numpy
  import pandas
  import pytest
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import ARG, COLUMN, METHOD, ROW_INDEX, TRUE_Y, MatrixParams, Metrics, ModelTask, f1_metrics, metric_to_display_name, precision_metrics, recall_metrics
  from erroranalysis._internal.error_analyzer import ModelAnalyzer
  from erroranalysis._internal.matrix_filter import CATEGORY1, CATEGORY2, COUNT, FALSE_COUNT, FN, FP, INTERVAL_MAX, INTERVAL_MIN, MATRIX, METRIC_NAME, METRIC_VALUE, TN, TP, VALUES, bin_data
  from erroranalysis._internal.metrics import get_ordered_classes, is_multi_agg_metric, metric_to_func
  from rai_test_utils.datasets.tabular import create_adult_census_data, create_binary_classification_dataset, create_cancer_data, create_diabetes_data, create_housing_data, create_iris_data, create_simple_titanic_data, create_wine_data
  from rai_test_utils.models.model_utils import create_models_classification, create_models_regression
  from rai_test_utils.models.sklearn import create_kneighbors_classifier, create_titanic_pipeline
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 6 for calling the TestMatrixFilter obj's underlying member method code with example usage: obj.test_matrix_filter_adult_census_quantile_binning(string_labels, metric) without return types