class_docstr: Estimate the univariate drift between two datasets.
  
  Estimate the univariate drift between two datasets
  and select features with low drifts
  
  Parameters
  ----------
  threshold : float, defaut = 0.6
      The drift threshold (univariate drift below are kept)
      Must be between 0. and 1.
  
  subsample : float, defaut = 1.
      Subsampling parameter for the datasets.
      Must be between 0. and 1.
  
  estimator : classifier, default = DecisionTreeClassifier(max_depth=6)
      The estimator that estimates the drift between two datasets.
  
  n_folds : int, default = 2
      Number of folds used to estimate the drift.
  
  stratify : bool, default = True
      Whether the cv is stratified (same number of train and test samples
      within each fold)
  
  random_state : int, default = 1
      Seed for for cv and subsampling.
  
  n_jobs : int, defaut = -1
      Number of cores used for processing (-1 for all cores)
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docstr: Set parameters of a DriftThreshold object.
docstr_tok: ["Set","parameters","of","a","DriftThreshold","object","."]
code: def set_params(self, **params):
      """Set parameters of a DriftThreshold object."""
      if "threshold" in params.keys():
          self.threshold = params["threshold"]
      if "subsample" in params.keys():
          self.subsample = params["subsample"]
      if "estimator" in params.keys():
          self.estimator = params["estimator"]
      if "n_folds" in params.keys():
          self.n_folds = params["n_folds"]
      if "stratify" in params.keys():
          self.stratify = params["stratify"]
      if "random_state" in params.keys():
          self.random_state = params["random_state"]
      if "n_jobs" in params.keys():
          self.n_jobs = params["n_jobs"]
  
file_path: MLBox/mlbox/preprocessing/drift/drift_threshold.py
imports: import sys
  from joblib import Parallel, delayed
  from sklearn.tree import DecisionTreeClassifier
  from .drift_estimator import DriftEstimator
label_desc: Use image node_id 3 for calling the DriftThreshold obj's underlying member method code with example usage: obj.set_params() without return types