class_docstr: Abstract class for all combination classes.
  
  Parameters
  ----------
  base_estimators: list, length must be greater than 1
      A list of base estimators. Certain methods must be present, e.g.,
      `fit` and `predict`.
  
  pre_fitted: bool, optional (default=False)
      Whether the base estimators are trained. If True, `fit`
      process may be skipped.
docstr: Internal function to predict if a particular sample is an
  outlier or not.
  
  Parameters
  ----------
  X : numpy array of shape (n_samples, n_features)
      The input samples.
  
  Returns
  -------
  outlier_labels : numpy array of shape (n_samples,)
      For each observation, tells whether or not
      it should be considered as an outlier according to the
      fitted model. 0 stands for inliers and 1 for outliers.
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code: def _detector_predict(self, X):
      """Internal function to predict if a particular sample is an
      outlier or not.
  
      Parameters
      ----------
      X : numpy array of shape (n_samples, n_features)
          The input samples.
  
      Returns
      -------
      outlier_labels : numpy array of shape (n_samples,)
          For each observation, tells whether or not
          it should be considered as an outlier according to the
          fitted model. 0 stands for inliers and 1 for outliers.
      """
  
      check_is_fitted(
          self, ["decision_scores_", "threshold_", "labels_"]
      )
  
      pred_score = self.decision_function(X)
      return (pred_score > self.threshold_).astype("int").ravel()
  
imports: import warnings
  from collections import defaultdict
  from abc import ABC, abstractmethod
  import numpy
  from numpy import percentile
  from scipy.special import erf
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.utils import column_or_1d
  from sklearn.utils.validation import check_is_fitted
  from sklearn.utils.multiclass import check_classification_targets
  from .sklearn_base import _pprint
  from inspect import signature
label_desc: Use image node_id 7 for calling the BaseAggregator obj's underlying member method code with example usage: obj._detector_predict(X) and returns: unknown