class_docstr: Estimates the drift between two datasets
  
      
  Parameters
  ----------
  estimator : classifier, defaut = RandomForestClassifier(n_estimators = 50, n_jobs=-1, max_features=1., min_samples_leaf = 5, max_depth = 5)
      The estimator that estimates the drift between two datasets
      
  n_folds : int, defaut = 2
      Number of folds used to estimate the drift
  
  stratify : bool, defaut = True
      Whether the cv is stratified (same number of train and test samples within each fold)
  
  random_state : int, defaut = 1
      Random state for cv
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docstr: Returns the global drift measure between two datasets.
  
   0. = No drift. 1. = Maximal Drift
  
  Returns
  -------
  float
      The drift measure
docstr_tok: ["Returns","the","global","drift","measure","between","two","datasets",".","0",".","=","No","drift",".","1",".","=","Maximal","Drift","Returns","--","--","--","-","float","The","drift","measure"]
code: def score(self):
      """Returns the global drift measure between two datasets.
  
       0. = No drift. 1. = Maximal Drift
  
      Returns
      -------
      float
          The drift measure
      """
  
      S = []
  
      if self.__fitOK:
          X_zeros = np.zeros(len(self.__target))
  
          for train_index, test_index in self.__cv.split(
              X=X_zeros, y=self.__target
          ):
              S.append(
                  roc_auc_score(
                      self.__target.iloc[test_index],
                      self.__pred[test_index],
                  )
              )
  
          return (max(np.mean(S), 1 - np.mean(S)) - 0.5) * 2
  
      else:
          raise ValueError("Call the fit function before !")
  
file_path: MLBox/mlbox/preprocessing/drift/drift_estimator.py
imports: import numpy
  import pandas
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import KFold, StratifiedKFold, cross_val_predict
label_desc: Use image node_id 5 for calling the DriftEstimator obj's underlying member method code with example usage: obj.score() and returns: unknown