code: def svm_svmguide1():
      svmguide1 = h2o.import_file(
          pyunit_utils.locate("smalldata/svm_test/svmguide1.svm")
      )
      svmguide1_test = h2o.import_file(
          pyunit_utils.locate("smalldata/svm_test/svmguide1_test.svm")
      )
  
      # response is not -1/1 - needs to be explicitly converted
      svmguide1["C1"] = svmguide1["C1"].asfactor()
      svmguide1_test["C1"] = svmguide1_test["C1"].asfactor()
  
      svm = H2OSupportVectorMachineEstimator(
          gamma=0.01, rank_ratio=0.1, disable_training_metrics=False
      )
      svm.train(
          y="C1",
          training_frame=svmguide1,
          validation_frame=svmguide1_test,
      )
      svm.show()
  
      pred = svm.predict(test_data=svmguide1)
      assert len(pred) == len(svmguide1)
  
      accuracy = svm.model_performance(valid=True).accuracy()[0][1]
      assert accuracy >= 0.95
  
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_svmguide1() without return types