class_docstr: Manages issues related to out-of-distribution examples.
class_docstr_tok: ["Manages","issues","related","to","out-of-distribution","examples","."]
code: def __init__(
      self,
      datalab: Datalab,
      threshold: Optional[float] = None,
      **kwargs,
  ):
      super().__init__(datalab)
  
      ood_kwargs = kwargs.get("ood_kwargs", {})
  
      valid_ood_params = OutOfDistribution.DEFAULT_PARAM_DICT.keys()
      params = {
          key: value
          for key, value in (
              (k, kwargs.get(k, None)) for k in valid_ood_params
          )
          if value is not None
      }
  
      if params:
          ood_kwargs["params"] = params
  
      self.ood: OutOfDistribution = OutOfDistribution(**ood_kwargs)
  
      self.threshold = threshold
      self._embeddings: Optional[np.ndarray] = None
      self._metric: str = None
  
file_path: cleanlab/cleanlab/datalab/internal/issue_manager/outlier.py
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Tuple, Union, cast
  from scipy.sparse import csr_matrix
  from scipy.stats import iqr
  import numpy
  import pandas
  from cleanlab.datalab.internal.issue_manager import IssueManager
  from cleanlab.outlier import OutOfDistribution, transform_distances_to_scores
label_desc: Use image node_id 1 to create a new OutlierIssueManager object from inherited base classes: IssueManager with example: obj = OutlierIssueManager(datalab, threshold)