class_docstr: Applies standard scaling to the target.
  
  Parameters
  ----------
  regressor
      Regression model to wrap.
  
  Examples
  --------
  
  >>> from river import datasets
  >>> from river import evaluate
  >>> from river import linear_model
  >>> from river import metrics
  >>> from river import preprocessing
  
  >>> dataset = datasets.TrumpApproval()
  >>> model = (
  ...     preprocessing.StandardScaler() |
  ...     preprocessing.TargetStandardScaler(
  ...         regressor=linear_model.LinearRegression(intercept_lr=0.15)
  ...     )
  ... )
  >>> metric = metrics.MSE()
  
  >>> evaluate.progressive_val_score(dataset, model, metric)
  MSE: 2.005999
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code: def _scale(self, y):
      return safe_div(y - self.var.mean.get(), self.var.get() ** 0.5)
  
file_path: river/river/preprocessing/scale_target.py
imports: from __future__ import annotations
  import math
  from river import base, compose, stats
label_desc: Use image node_id 3 for calling the TargetStandardScaler obj's underlying member method code with example usage: obj._scale(y) and returns: safe_div