code: def svm_svmguide3():
      svmguide3 = h2o.import_file(
          pyunit_utils.locate("smalldata/svm_test/svmguide3scale.svm")
      )
      svmguide3_test = h2o.import_file(
          pyunit_utils.locate(
              "smalldata/svm_test/svmguide3scale_test.svm"
          )
      )
  
      # parameters taken from libsvm guide
      svm_tuned = H2OSupportVectorMachineEstimator(
          hyper_param=128, gamma=0.125, disable_training_metrics=False
      )
      svm_tuned.train(
          y="C1",
          training_frame=svmguide3,
          validation_frame=svmguide3_test,
      )
  
      accuracy = svm_tuned.model_performance(valid=True).accuracy()[0][
          1
      ]
      assert accuracy >= 0.80
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.psvm import H2OSupportVectorMachineEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: svm_svmguide3() without return types