code: def test_error_analysis_iris_numeric_feature_names(self):
      # e2e test of error analysis with numeric feature names
      X_train, X_test, y_train, y_test, _, _ = create_iris_data()
      knn = sklearn.neighbors.KNeighborsClassifier()
      knn.fit(X_train, y_train)
  
      model_task = ModelTask.Classification
      explainer = MimicExplainer(
          knn, X_train, LGBMExplainableModel, model_task=model_task
      )
      global_explanation = explainer.explain_global(X_test)
  
      dashboard = ErrorAnalysisDashboard(
          global_explanation, knn, dataset=X_test, true_y=y_test
      )
      metric = metric_to_display_name[Metrics.ERROR_RATE]
      result = dashboard.input.debug_ml(
          [
              global_explanation.features,
              [],
              [],
              DEFAULT_MAX_DEPTH,
              DEFAULT_NUM_LEAVES,
              DEFAULT_MIN_CHILD_SAMPLES,
              metric,
          ]
      )
      assert WidgetRequestResponseConstants.ERROR not in result
      matrix_features = global_explanation.features[0:1]
      result = dashboard.input.matrix(
          matrix_features, [], [], True, 8, metric
      )
      assert WidgetRequestResponseConstants.ERROR not in result
  
imports: import numpy
  import pandas
  import shap
  import sklearn
  from interpret.ext.blackbox import MimicExplainer
  from interpret.ext.glassbox import LGBMExplainableModel
  from interpret_community.common.constants import ModelTask
  from sklearn.datasets import load_iris, make_classification
  from sklearn.model_selection import train_test_split
  from erroranalysis._internal.constants import Metrics, metric_to_display_name
  from erroranalysis._internal.surrogate_error_tree import DEFAULT_MAX_DEPTH, DEFAULT_MIN_CHILD_SAMPLES, DEFAULT_NUM_LEAVES
  from raiwidgets import ErrorAnalysisDashboard
  from raiwidgets.explanation_constants import WidgetRequestResponseConstants
label_desc: Use image node_id 5 for calling the TestErrorAnalysisDashboard obj's underlying member method code with example usage: obj.test_error_analysis_iris_numeric_feature_names() without return types