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 covariance(self) -> float:
      return self.gh_cov.get()
  
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 9 for calling the GradHessStats obj's underlying member method code with example usage: obj.covariance() and returns: self