code: def testFeatureNamesAndCategoricalFeats(self):
      training_data = np.array([[0.0, 1.0], [1.0, 0.0]])
  
      explainer = LimeTabularExplainer(training_data=training_data)
      self.assertEqual(explainer.feature_names, ["0", "1"])
      self.assertEqual(explainer.categorical_features, [0, 1])
  
      explainer = LimeTabularExplainer(
          training_data=training_data,
          feature_names=np.array(["one", "two"]),
      )
      self.assertEqual(explainer.feature_names, ["one", "two"])
  
      explainer = LimeTabularExplainer(
          training_data=training_data,
          categorical_features=np.array([0]),
          discretize_continuous=False,
      )
      self.assertEqual(explainer.categorical_features, [0])
  
imports: import unittest
  import numpy
  import collections
  import sklearn
  import sklearn.datasets
  import sklearn.ensemble
  import sklearn.linear_model
  from numpy.testing import assert_array_equal
  from sklearn.datasets import load_iris, make_classification, make_multilabel_classification
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import LinearRegression
  from lime.discretize import QuartileDiscretizer, DecileDiscretizer, EntropyDiscretizer
  from lime.lime_tabular import LimeTabularExplainer
label_desc: Use image node_id 9 for calling the TestLimeTabular obj's underlying member method code with example usage: obj.testFeatureNamesAndCategoricalFeats() without return types