class_docstr: sklearn removes the leading 2 from the gradient of the squared loss.
class_docstr_tok: ["sklearn","removes","the","leading","2","from","the","gradient","of","the","squared","loss","."]
code: def gradient(self, y_true, y_pred):
      return y_pred - y_true
  
imports: from __future__ import annotations
  import copy
  import itertools
  import math
  import random
  import numpy
  import pandas
  import pytest
  from sklearn import linear_model
  from sklearn.datasets import make_classification, make_regression
  from sklearn.metrics import log_loss
  from river import datasets, optim, preprocessing, stream, utils
  from river import linear_model
label_desc: Use image node_id 1 for calling the ScikitLearnSquaredLoss obj's underlying member method code with example usage: obj.gradient(y_true, y_pred) and returns: unknown