code: def xgboost_feature_interactions():
      prostate_frame = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      y = "RACE"
      ignored_columns = ["ID"]
  
      model = H2OXGBoostEstimator(
          training_frame=prostate_frame, seed=0xDECAF
      )
      model.train(
          y=y,
          ignored_columns=ignored_columns,
          training_frame=prostate_frame,
      )
  
      feature_interactions = model.feature_interaction(2, 100, -1)
      assert isinstance(feature_interactions[0], H2OTwoDimTable)
      assert len(feature_interactions) == 11
  
      path = pyunit_utils.locate("results")
      feature_interactions = model.feature_interaction(
          2, 100, -1, os.path.join(path, "feature_interactions.xlsx")
      )
      assert isinstance(feature_interactions[0], H2OTwoDimTable)
      assert len(feature_interactions) == 11
      assert os.path.exists(
          os.path.join(path, "feature_interactions.xlsx")
      )
      os.remove(os.path.join(path, "feature_interactions.xlsx"))
  
imports: from h2o.estimators.xgboost import *
  from tests import pyunit_utils, os
  import sys
  from h2o.two_dim_table import H2OTwoDimTable
label_desc: Use image node_id 1 for calling a global function with example usage: xgboost_feature_interactions() without return types