docstr: Set the parameters of this estimator.
docstr_tok: ["Set","the","parameters","of","this","estimator","."]
code: def set_params(self, **params):
      """
      Set the parameters of this estimator.
      """
      for param in params:
          if hasattr(self, param):
              setattr(self, param, params[param])
      return self
  
imports: import time
  import numpy
  import pandas
  from sklearn.base import BaseEstimator
  from sklearn.feature_selection import SelectorMixin
  from sklearn.utils.validation import check_is_fitted
  import torch
  from nni.feature_engineering.feature_selector import FeatureSelector
  from .None import constants
  from .fginitialize import PrepareData
  from .fgtrain import _train
label_desc: Use image node_id 15 for calling the FeatureGradientSelector obj's underlying member method code with example usage: obj.set_params() and returns: self