code: def shrink(self, reg_param, cum_sum=0):
      if self.is_root:
          cum_sum = self.value
      if self.left is None:  # if leaf node, change prediction
          self.value = cum_sum
      else:
          shrunk_diff = (self.left.value - self.value) / (
              1 + reg_param / self.n_samples
          )
          self.left.shrink(reg_param, cum_sum + shrunk_diff)
          shrunk_diff = (self.right.value - self.value) / (
              1 + reg_param / self.n_samples
          )
          self.right.shrink(reg_param, cum_sum + shrunk_diff)
  
imports: from copy import deepcopy
  import numpy
  from matplotlib import pyplot
  from sklearn import datasets
  from sklearn import tree
  from sklearn.base import BaseEstimator
  from sklearn.linear_model import RidgeCV, RidgeClassifierCV
  from sklearn.model_selection import train_test_split
  from sklearn.tree import plot_tree
  from sklearn.utils import check_X_y
  from imodels.tree.viz_utils import extract_sklearn_tree_from_figs
label_desc: Use image node_id 3 for calling the Node obj's underlying member method code with example usage: obj.shrink(reg_param, cum_sum) without return types