code: def test_regression_ignore_format(df_enc_numeric):
      random = np.random.RandomState(42)
      y = random.normal(0, 0.1, len(df_enc_numeric))
      encoder = DecisionTreeEncoder(
          regression=True,
          random_state=random,
          ignore_format=True,
      )
      encoder.fit(df_enc_numeric[["var_A", "var_B"]], y)
      X = encoder.transform(df_enc_numeric[["var_A", "var_B"]])
  
      transf_df = df_enc_numeric.copy()
      transf_df["var_A"] = (
          [0.034348] * 6 + [-0.024679] * 10 + [-0.075473] * 4
      )  # Tree: var_A <= 1.5 -> 0.25 else 0.5
      transf_df["var_B"] = [0.044806] * 10 + [-0.079066] * 10
      pd.testing.assert_frame_equal(
          X.round(6), transf_df[["var_A", "var_B"]]
      )
  
file_path: feature_engine/tests/test_encoding/test_decision_tree_encoder.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.encoding import DecisionTreeEncoder
label_desc: Use image node_id 8 for calling a global function with example usage: test_regression_ignore_format(df_enc_numeric) without return types