code: def get_algorithms(algorithm):
      
      if algorithm == util_functions.AlgorithmTypes.classification:
          clf = sklearn.ensemble.GradientBoostingClassifier(n_estimators=100, learn_rate=.05,
              max_depth=4, random_state=1,min_samples_leaf=3)
          clf2=sklearn.ensemble.GradientBoostingClassifier(n_estimators=100, learn_rate=.05,
              max_depth=4, random_state=1,min_samples_leaf=3)
      else:
          clf = sklearn.ensemble.GradientBoostingRegressor(n_estimators=100, learn_rate=.05,
              max_depth=4, random_state=1,min_samples_leaf=3)
          clf2=sklearn.ensemble.GradientBoostingRegressor(n_estimators=100, learn_rate=.05,
              max_depth=4, random_state=1,min_samples_leaf=3)
      return clf, clf2
docs: Gets two classifiers for each type of algorithm, and returns them.  First for predicting, second for cv error.
      type - one of util_functions.AlgorithmTypes