code: def setUp(self):
      self.model_list = [
          xgb.XGBClassifier(n_estimators=1),
          ske.RandomForestClassifier(n_estimators=1),
          ske.RandomForestRegressor(n_estimators=1),
          ske.GradientBoostingRegressor(n_estimators=1),
      ]
  
      df = pd.DataFrame(range(0, 4), columns=["id"])
      df["y"] = df["id"].apply(lambda x: 1 if x < 3 else 0)
      df["x1"] = np.random.randint(1, 123, df.shape[0])
      df["x2"] = np.random.randint(1, 3, df.shape[0])
      df = df.set_index("id")
      self.x_df = df[["x1", "x2"]]
      self.y_df = df["y"].to_frame()
  
file_path: shapash/tests/unit_tests/backend/test_lime_backend.py
imports: import unittest
  import numpy
  import pandas
  import sklearn.ensemble
  import xgboost
  import category_encoders
  from shapash.backend.lime_backend import LimeBackend
label_desc: Use image node_id 1 for calling the TestLimeBackend obj's underlying member method code with example usage: obj.setUp() without return types