docstr: Compute outlier scores.
  
  Parameters
  ----------
  X
      Batch of instances to analyze.
  
  Returns
  -------
  Array with outlier scores for each instance in the batch.
docstr_tok: ["Compute","outlier","scores",".","Parameters","--","--","--","--","--","X","Batch","of","instances","to","analyze",".","Returns","--","--","--","-","Array","with","outlier","scores","for","each","instance","in","the","batch","."]
code: def score(self, X: np.ndarray) -> np.ndarray:
      """
      Compute outlier scores.
  
      Parameters
      ----------
      X
          Batch of instances to analyze.
  
      Returns
      -------
      Array with outlier scores for each instance in the batch.
      """
      return -self.isolationforest.decision_function(X)
  
file_path: alibi-detect/alibi_detect/od/isolationforest.py
imports: import logging
  import numpy
  from sklearn.ensemble import IsolationForest
  from typing import Dict, Union
  from alibi_detect.base import BaseDetector, FitMixin, ThresholdMixin, outlier_prediction_dict
label_desc: Use image node_id 4 for calling the IForest obj's underlying member method code with example usage: obj.score(X) and returns: unknown