class_docstr: Class used to monitor and update the gradient/hessian information in Stochastic Gradient
  Trees.
  
  Represents the aggregated gradient/hessian data in a node (global node statistics), category,
  or numerical feature's discretized bin.
code: def __sub__(self, other):
      new = copy.deepcopy(self)
      new -= other
  
      return new
  
imports: from __future__ import annotations
  import collections
  import copy
  import dataclasses
  import functools
  import math
  import sys
  import typing
  from river.base.typing import FeatureName
  from river.stats import Cov, Var
label_desc: Use image node_id 5 for calling the GradHessStats obj's underlying member method code with example usage: obj.__sub__(other) and returns: new