class_docstr: Base class for Bagging meta-estimator.
  
  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: import itertools
  import numbers
  from abc import ABCMeta, abstractmethod
  from functools import partial
  from numbers import Integral
  from warnings import warn
  import numpy
  from ..base import ClassifierMixin, RegressorMixin, _fit_context
  from ..metrics import accuracy_score, r2_score
  from ..tree import DecisionTreeClassifier, DecisionTreeRegressor
  from ..utils import check_random_state, column_or_1d, indices_to_mask
  from ..utils._param_validation import HasMethods, Interval, RealNotInt
  from ..utils._tags import _safe_tags
  from ..utils.metadata_routing import _raise_for_unsupported_routing, _RoutingNotSupportedMixin
  from ..utils.metaestimators import available_if
  from ..utils.multiclass import check_classification_targets
  from ..utils.parallel import Parallel, delayed
  from ..utils.random import sample_without_replacement
  from ..utils.validation import _check_sample_weight, check_is_fitted, has_fit_parameter
  from ._base import BaseEnsemble, _partition_estimators
label_desc: Use image node_id 5 for calling the BaseBagging obj's underlying member method code with example usage: obj._set_oob_score(X, y) without return types