code: def scale_svd_rf_pipe_new_import():
      from h2o.estimators.svd import (
          H2OSingularValueDecompositionEstimator,
      )
  
      print("Importing USArrests.csv data...")
      arrests = h2o.upload_file(
          pyunit_utils.locate("smalldata/pca_test/USArrests.csv")
      )
  
      print("Compare with SVD")
  
      # build  transformation pipeline using sklearn's Pipeline and H2OSingularValueDecompositionEstimator
      pipe = Pipeline(
          [
              ("standardize", H2OScaler()),
              # H2OSingularValueDecompositionEstimator() call will fail, you have to call init_for_pipeline method
              (
                  "svd",
                  H2OSingularValueDecompositionEstimator().init_for_pipeline(),
              ),
              ("rf", H2ORandomForestEstimator()),
          ]
      )
  
      params = {
          "standardize__center": [True, False],
          "standardize__scale": [True, False],
          "svd__nv": [2, 3],
          "rf__ntrees": randint(50, 60),
          "rf__max_depth": randint(4, 8),
          "rf__min_rows": randint(5, 10),
          "svd__transform": ["none", "standardize"],
      }
  
      custom_cv = H2OKFold(arrests, n_folds=5, seed=42)
      random_search = RandomizedSearchCV(
          pipe,
          params,
          n_iter=5,
          scoring=make_scorer(h2o_r2_score),
          cv=custom_cv,
          random_state=42,
          n_jobs=1,
      )
  
      random_search.fit(arrests[1:], arrests[0])
      print(random_search.best_estimator_)
  
file_path: h2o-3/h2o-py/tests/testdir_scikit_grid/pyunit_scal_svd_rf_grid.py
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.transforms.preprocessing import H2OScaler
  from h2o.estimators.random_forest import H2ORandomForestEstimator
  from sklearn.pipeline import Pipeline
  from sklearn.model_selection import RandomizedSearchCV
  from h2o.cross_validation import H2OKFold
  from h2o.model.regression import h2o_r2_score
  from sklearn.metrics import make_scorer
  from scipy.stats import randint
label_desc: Use image node_id 2 for calling a global function with example usage: scale_svd_rf_pipe_new_import() without return types