class_docstr: Loss function used in regression tasks.
class_docstr_tok: ["Loss","function","used","in","regression","tasks","."]
code: def compute_derivatives(self, y_true, y_pred):
      return GradHess(y_pred - y_true, 1.0)
  
file_path: river/river/tree/losses.py
imports: from __future__ import annotations
  import abc
  import math
  from .utils import GradHess
label_desc: Use image node_id 1 for calling the SquaredErrorLoss obj's underlying member method code with example usage: obj.compute_derivatives(y_true, y_pred) and returns: GradHess