message: CLN: normalize is False by default
diff: @@ -956,9 +956,7 @@ def _compute_feature_importances_per_tree(tree, num_features):
  return importances
  -def _compute_feature_importances(tree_ensemble,
  - num_features,
  - normalize=True):
  +def _compute_feature_importances(tree_ensemble, num_features, normalize):
  """Compute the feature importances.
  The higher the value, the more important the feature.
  @@ -972,6 +970,9 @@ def _compute_feature_importances(tree_ensemble,
  sorted_feature_idx: A list of feature_id which is sorted
  by its feature importance.
  feature_importances: A list of corresponding feature importance.
  +
  + Raises:
  + AssertionError: Trees are all empty or root node only when normalizing.
  """
  tree_importances = [_compute_feature_importances_per_tree(tree, num_features)
  for tree in tree_ensemble.trees]
  @@ -996,7 +997,7 @@ class _BoostedTrees(estimator.Estimator):
  self._sorted_feature_columns = sorted(feature_columns, key=lambda tc: tc.name)
  - def experimental_feature_importances(self, normalize=True):
  + def experimental_feature_importances(self, normalize=False):
  """Compute the feature importances.
  The higher the value, the more important the corresponding feature.
  @@ -1005,9 +1006,9 @@ class _BoostedTrees(estimator.Estimator):
  normalize: If True, normalize the feature importances.
  Returns:
  - sorted_feature_names: A list of feature name which is sorted
  + sorted_feature_names: 1-D array of feature name which is sorted
  by its feature importance.
  - feature_importances: A list of corresponding feature importance.
  + feature_importances: 1-D array of the corresponding feature importance.
  Raises:
  ValueError: Empty ensemble.
  