class_docstr: Cauchy loss function.
  
  Parameters
  ----------
  C
  
  References
  ----------
  [^1]: ["Effect of MAE" Kaggle discussion](https://www.kaggle.com/c/allstate-claims-severity/discussion/24520#140163)
  [^2]: [Paris Madness Kaggle kernel](https://www.kaggle.com/raddar/paris-madness)
class_docstr_tok: ["Cauchy","loss","function",".","Parameters","--","--","--","--","--","C","References","--","--","--","--","--","[","^1","]",":","[","``","Effect","of","MAE","''","Kaggle","discussion","]","(","https",":","\/\/www.kaggle.com\/c\/allstate-claims-severity\/discussion\/24520","#","140163",")","[","^2","]",":","[","Paris","Madness","Kaggle","kernel","]","(","https",":","\/\/www.kaggle.com\/raddar\/paris-madness",")"]
code: def __init__(self, C=80):
      self.C = C
  
imports: from __future__ import annotations
  import math
  import numpy
  from scipy import special
  from river import base, utils
  from river.optim.base import Loss
label_desc: Use image node_id 1 to create a new Cauchy object from inherited base classes: RegressionLoss with example: obj = Cauchy(C)