class_docstr: Base class for sklearn backend outlier detection algorithms.
class_docstr_tok: ["Base","class","for","sklearn","backend","outlier","detection","algorithms","."]
docstr: Score the data.
  
  Parameters
  ----------
  x
      Data to score.
docstr_tok: ["Score","the","data",".","Parameters","--","--","--","--","--","x","Data","to","score","."]
code: def score(self, x: np.ndarray) -> np.ndarray:
      """Score the data.
  
      Parameters
      ----------
      x
          Data to score.
  
      """
      pass
  
imports: from typing import List, Union, Optional, Dict
  from dataclasses import dataclass, asdict
  from abc import ABC, abstractmethod
  from typing_extensions import Self
  import numpy
  from alibi_detect.exceptions import NotFittedError, ThresholdNotInferredError
label_desc: Use image node_id 1 for calling the SklearnOutlierDetector obj's underlying member method code with example usage: obj.score(x) without return types