code: def nb_init_err():
      print("Importing iris_wheader.csv data...\n")
      iris = h2o.upload_file(
          pyunit_utils.locate("smalldata/iris/iris_wheader.csv")
      )
      iris.describe
  
      print("Laplace smoothing parameter is negative")
  
      try:
          H2ONaiveBayesEstimator(laplace=-1).train(
              x=list(range(4)), y=4, training_frame=iris
          )
          assert (
              False
          ), "Expected naive bayes algo to fail on negative laplace training parameter"
      except:
          pass
  
      print("Minimum standard deviation is zero")
      try:
          H2ONaiveBayesEstimator().train(
              x=list(range(4)), y=4, training_frame=iris, min_sdev=0
          )
          assert (
              False
          ), "Expected naive bayes algo to fail on min_sdev = 0"
      except:
          pass
  
      print("Response column is not categorical")
      try:
          H2ONaiveBayesEstimator().train(
              x=list(range(3)), y=3, min_sdev=0
          )
          assert (
              False
          ), "Expected naive bayes algo to fail on response not categorical"
      except:
          pass
  
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.naive_bayes import H2ONaiveBayesEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: nb_init_err() without return types