code: def test_empty_cohort_diabetes_regression(self, analyzer_type):
      (
          X_train,
          X_test,
          y_train,
          y_test,
          feature_names,
      ) = create_diabetes_data()
  
      model = create_kneighbors_classifier(X_train, y_train)
  
      composite_filters = [
          {
              COMPOSITE_FILTERS: [
                  {
                      COMPOSITE_FILTERS: [
                          {
                              ARG: [0.06],
                              COLUMN: "s1",
                              METHOD: CohortFilterMethods.METHOD_GREATER,
                          },
                          {
                              ARG: [-0.01],
                              COLUMN: "s2",
                              METHOD: CohortFilterMethods.METHOD_LESS,
                          },
                      ],
                      OPERATION: CohortFilterOps.AND,
                  }
              ],
              OPERATION: CohortFilterOps.OR,
          }
      ]
      run_error_analyzer(
          model,
          X_test,
          y_test,
          feature_names,
          analyzer_type,
          composite_filters=composite_filters,
      )
  
imports: import re
  import time
  from enum import Enum
  import numpy
  import pandas
  import pytest
  from common_utils import replicate_dataset
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import ARG, COLUMN, COMPOSITE_FILTERS, DIFF, LEAF_INDEX, METHOD, OPERATION, PRED_Y, ROW_INDEX, SPLIT_FEATURE, SPLIT_INDEX, TRUE_Y, CohortFilterMethods, CohortFilterOps, Metrics, ModelTask, regression_metrics
  from erroranalysis._internal.error_analyzer import ModelAnalyzer, PredictionsAnalyzer
  from erroranalysis._internal.surrogate_error_tree import TreeSide, cache_subtree_features, compute_error_tree, create_surrogate_model, get_categorical_info, get_max_split_index, traverse
  from rai_test_utils.datasets.tabular import create_adult_census_data, create_binary_classification_dataset, create_cancer_data, create_diabetes_data, create_iris_data, create_simple_titanic_data
  from rai_test_utils.models.model_utils import create_models_classification
  from rai_test_utils.models.sklearn import create_kneighbors_classifier, create_sklearn_random_forest_regressor, create_titanic_pipeline
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 8 for calling the TestSurrogateErrorTree obj's underlying member method code with example usage: obj.test_empty_cohort_diabetes_regression(analyzer_type) without return types