code: def test_parameters(
      self,
      metric,
      min_child_samples,
      max_depth,
      num_leaves,
      analyzer_type,
  ):
      (
          X_train,
          X_test,
          y_train,
          y_test,
          feature_names,
          _,
      ) = create_iris_data()
  
      model = create_kneighbors_classifier(X_train, y_train)
      run_error_analyzer(
          model,
          X_test,
          y_test,
          feature_names,
          analyzer_type,
          max_depth=max_depth,
          num_leaves=num_leaves,
          min_child_samples=min_child_samples,
          metric=metric,
      )
  
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 6 for calling the TestSurrogateErrorTree obj's underlying member method code with example usage: obj.test_parameters(metric, min_child_samples, max_depth, num_leaves, analyzer_type) without return types