code: def adaboost():
      print("AdaBoost Smoke Test")
  
      train = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      train["CAPSULE"] = train["CAPSULE"].asfactor()
  
      adaboost_model = H2OAdaBoostEstimator(
          nlearners=55, seed=0xBEEF, weak_learner="GLM", learn_rate=0.6
      )
      adaboost_model.train(training_frame=train, y="CAPSULE")
      predict = adaboost_model.predict(train)
  
      print("")
      print(adaboost_model)
      print("")
      print(predict)
  
      assert (
          55
          == adaboost_model._model_json["output"]["model_summary"][
              "number_of_weak_learners"
          ][0]
      ), "Python API is not working!"
      assert (
          "GLM"
          == adaboost_model._model_json["output"]["model_summary"][
              "weak_learner"
          ][0]
      ), "Python API is not working!"
      assert (
          0.6
          == adaboost_model._model_json["output"]["model_summary"][
              "learn_rate"
          ][0]
      ), "Python API is not working!"
  
imports: import sys, os
  import h2o
  from tests import pyunit_utils
  from h2o.estimators import H2OAdaBoostEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: adaboost() without return types