class_docstr: Binary logarithmic loss.
  
  Examples
  --------
  
  >>> from river import metrics
  
  >>> y_true = [True, False, False, True]
  >>> y_pred = [0.9,  0.1,   0.2,   0.65]
  
  >>> metric = metrics.LogLoss()
  >>> for yt, yp in zip(y_true, y_pred):
  ...     metric.update(yt, yp)
  ...     print(metric.get())
  0.105360
  0.105360
  0.144621
  0.216161
  
  >>> metric
  LogLoss: 0.216162
code: def bigger_is_better(self):
      return False
  
file_path: river/river/metrics/log_loss.py
imports: from __future__ import annotations
  import math
  from river import metrics
label_desc: Use image node_id 1 for calling the LogLoss obj's underlying member method code with example usage: obj.bigger_is_better() and returns: False