class_docstr: Base Stochastic Gradient Tree (SGT) class.
  
  This class defines the main characteristics that are shared by the different SGT
  implementations.
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docstr: Apply transformation to the raw target input.
  
  Different strategies are used for classification and regression. By default, use
  an identity function.
  
  Parameters
  ----------
  y
      The target value, over which the transformation will be applied.
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code: def _target_transform(self, y):
      """Apply transformation to the raw target input.
  
      Different strategies are used for classification and regression. By default, use
      an identity function.
  
      Parameters
      ----------
      y
          The target value, over which the transformation will be applied.
      """
      return y
  
imports: from __future__ import annotations
  import abc
  import math
  from scipy.stats import f
  from river import base, tree
  from .losses import BinaryCrossEntropyLoss, SquaredErrorLoss
  from .nodes.branch import DTBranch, NominalMultiwayBranch, NumericBinaryBranch
  from .nodes.sgt_nodes import SGTLeaf
  from .utils import BranchFactory, GradHessMerit
label_desc: Use image node_id 2 for calling the StochasticGradientTree obj's underlying member method code with example usage: obj._target_transform(y) and returns: y