class_docstr: Base class for forests of trees.
  
  Warning: This class should not be used directly. Use derived classes
  instead.
class_docstr_tok: ["Base","class","for","forests","of","trees",".","Warning",":","This","class","should","not","be","used","directly",".","Use","derived","classes","instead","."]
docstr: Calculate out of bag predictions and score.
docstr_tok: ["Calculate","out","of","bag","predictions","and","score","."]
code: def _set_oob_score(self, X, y):
      """Calculate out of bag predictions and score."""
  
imports: from __future__ import division
  import warnings
  from warnings import warn
  from abc import ABCMeta, abstractmethod
  import numpy
  from scipy.sparse import issparse
  from scipy.sparse import hstack
  from ..base import ClassifierMixin, RegressorMixin
  from ..externals.joblib import Parallel, delayed
  from ..externals import six
  from ..feature_selection.from_model import _LearntSelectorMixin
  from ..metrics import r2_score
  from ..preprocessing import OneHotEncoder
  from ..tree import DecisionTreeClassifier, DecisionTreeRegressor, ExtraTreeClassifier, ExtraTreeRegressor
  from ..tree._tree import DTYPE, DOUBLE
  from ..utils import check_random_state, check_array, compute_sample_weight
  from ..exceptions import DataConversionWarning, NotFittedError
  from .base import BaseEnsemble, _partition_estimators
  from ..utils.fixes import bincount, parallel_helper
  from ..utils.multiclass import check_classification_targets
label_desc: Use image node_id 5 for calling the BaseForest obj's underlying member method code with example usage: obj._set_oob_score(X, y) without return types