code: def test_set_paramns():
      """ """
      forecaster = ForecasterAutoregCustom(
          regressor=LinearRegression(fit_intercept=True),
          fun_predictors=create_predictors,
          window_size=5,
      )
      new_params = {"fit_intercept": False}
      forecaster.set_params(new_params)
      expected = {
          "copy_X": True,
          "fit_intercept": False,
          "n_jobs": None,
          "normalize": "deprecated",  # For sklearn < 1.2
          "positive": False,
      }
      results = forecaster.regressor.get_params()
      results.update({"normalize": "deprecated"})
      assert results == expected
  
imports: import pandas
  from skforecast.ForecasterAutoregCustom import ForecasterAutoregCustom
  from sklearn.linear_model import LinearRegression
label_desc: Use image node_id 2 for calling a global function with example usage: test_set_paramns() without return types