code: def glm_plot_test():
      prostate = h2o.import_file(
          pyunit_utils.locate("smalldata/logreg/prostate.csv")
      )
      prostate["DPROS"] = prostate["DPROS"].asfactor()
  
      glm_bin = H2OGeneralizedLinearEstimator(family="binomial")
      glm_bin.train(
          ignored_columns=["ID"], y="CAPSULE", training_frame=prostate
      )
      glm_bin.plot(server=True)
  
      glm_mult = H2OGeneralizedLinearEstimator(family="multinomial")
      glm_mult.train(
          ignored_columns=["ID"], y="DPROS", training_frame=prostate
      )
      glm_mult.plot(server=True)
  
      glm_reg = H2OGeneralizedLinearEstimator(
          family="gaussian",
          score_each_iteration=True,
          generate_scoring_history=True,
      )
      glm_reg.train(
          ignored_columns=["ID"], y="CAPSULE", training_frame=prostate
      )
      glm_reg.plot(server=True)
  
      glm_ord = H2OGeneralizedLinearEstimator(family="ordinal")
      glm_ord.train(
          ignored_columns=["ID"], y="DPROS", training_frame=prostate
      )
      glm_ord.plot(server=True)
  
imports: 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: glm_plot_test() without return types