class_docstr: Regression tree for XGBoost
  - Reference -
  http://xgboost.readthedocs.io/en/latest/model.html
class_docstr_tok: ["Regression","tree","for","XGBoost","-","Reference","-","http",":","\/\/xgboost.readthedocs.io\/en\/latest\/model.html"]
code: def _approximate_update(self, y):
      # y split into y, y_pred
      y, y_pred = self._split(y)
      # Newton's Method
      gradient = np.sum(y * self.loss.gradient(y, y_pred), axis=0)
      hessian = np.sum(self.loss.hess(y, y_pred), axis=0)
      update_approximation = gradient / hessian
  
      return update_approximation
  
imports: from __future__ import division, print_function
  import numpy
  from mlfromscratch.utils import divide_on_feature, train_test_split, standardize, mean_squared_error
  from mlfromscratch.utils import calculate_entropy, accuracy_score, calculate_variance
label_desc: Use image node_id 4 for calling the XGBoostRegressionTree obj's underlying member method code with example usage: obj._approximate_update(y) and returns: update_approximation