code: def test_glm_scoring_history_TomasF():
      df = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      df["CAPSULE"] = df["CAPSULE"].asfactor()
  
      glmModel = glm(generate_scoring_history=True)
      glmModel.train(y="CAPSULE", training_frame=df)
      glmModel.scoring_history()
  
imports: from past.utils import old_div
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_glm_scoring_history_TomasF() without return types