code: def set_params():
      missingValues = ["MeanImputation"]
      missing_values = missingValues[randint(0, len(missingValues) - 1)]
      reg = 1.0 / 250000.0
      params = {
          "missing_values_handling": missing_values,
          "family": "ordinal",
          "alpha": [0.5],
          "lambda_": [reg],
          "obj_reg": reg,
      }
      if uniform(0.0, 1.0) > 0.5:
          params["solver"] = "GRADIENT_DESCENT_SQERR"
      print(params)
      return params
  
imports: import sys, os
  import h2o
  from tests import pyunit_utils
  from random import randint
  from random import uniform
  import tempfile
label_desc: Use image node_id 2 for calling a global function with example usage: set_params() and returns: params