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 _gain(self, y, y_pred):
      nominator = np.power((y * self.loss.gradient(y, y_pred)).sum(), 2)
      denominator = self.loss.hess(y, y_pred).sum()
      return 0.5 * (nominator / denominator)
  
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 2 for calling the XGBoostRegressionTree obj's underlying member method code with example usage: obj._gain(y, y_pred) and returns: unknown