class_docstr: Logarithmic loss.
  
  This loss function expects each provided `y_pred` to be a logit. In other words if must be
  the raw output of a linear model or a neural network.
  
  Parameters
  ----------
  weight_pos
  weight_neg
  
  References
  ----------
  [^1]: [Logit Wikipedia page](https://www.wikiwand.com/en/Logit>)
class_docstr_tok: ["Logarithmic","loss",".","This","loss","function","expects","each","provided","`","y_pred","`","to","be","a","logit",".","In","other","words","if","must","be","the","raw","output","of","a","linear","model","or","a","neural","network",".","Parameters","--","--","--","--","--","weight_pos","weight_neg","References","--","--","--","--","--","[","^1","]",":","[","Logit","Wikipedia","page","]","(","https",":","\/\/www.wikiwand.com\/en\/Logit",">",")"]
code: def __init__(self, weight_pos=1.0, weight_neg=1.0):
      self.weight_pos = weight_pos
      self.weight_neg = weight_neg
  
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 Log object from inherited base classes: BinaryLoss with example: obj = Log(weight_pos, weight_neg)