class_docstr: Custom version ``LeaveOneGroupOut`` cross-validation iterator.
  
  This version only outputs indices of instances with IDs in a prespecified set.
  
  Parameters
  ----------
  keep : Iterable[IdType]
      A set of IDs to keep.
  example_ids : numpy.ndarray, of length n_samples
      A list of example IDs.
  logger : Optional[logging.Logger], default=None
      A logger instance.
docstr: Initialize the model.
docstr_tok: ["Initialize","the","model","."]
code: def __init__(
      self,
      keep: Iterable[IdType],
      example_ids: np.ndarray,
      logger: Optional[logging.Logger] = None,
  ):
      """Initialize the model."""
      super(FilteredLeaveOneGroupOut, self).__init__()
      self.keep = keep
      self.example_ids = example_ids
      self._warned = False
      self.logger = logger if logger else logging.getLogger(__name__)
  
imports: from __future__ import annotations
  import inspect
  import logging
  import sys
  import time
  from collections import Counter, defaultdict
  from csv import DictWriter, excel_tab
  from functools import wraps
  from importlib import import_module
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Set, Tuple, Type, Union
  import joblib
  import numpy
  import scipy.sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_selection import SelectKBest
  from sklearn.metrics import accuracy_score, confusion_matrix, precision_recall_fscore_support
  from sklearn.model_selection import KFold, LeaveOneGroupOut, ShuffleSplit, StratifiedKFold
  from skll.data import FeatureSet
  from skll.metrics import _CUSTOM_METRICS, _PREDEFINED_CUSTOM_METRICS, use_score_func
  from skll.types import ComputeEvalMetricsResults, ConfusionMatrix, FeaturesetIterator, FoldMapping, IdType, IndexIterator, LabelType, PathOrStr, SparseFeatureMatrix
  from skll.utils.constants import CLASSIFICATION_ONLY_METRICS, CORRELATION_METRICS, REGRESSION_ONLY_METRICS, UNWEIGHTED_KAPPA_METRICS, WEIGHTED_KAPPA_METRICS
  from skll.version import VERSION
label_desc: Use image node_id 1 to create a new FilteredLeaveOneGroupOut object from inherited base classes: LeaveOneGroupOut with example: obj = FilteredLeaveOneGroupOut(keep, example_ids, logger)