class_docstr: Root mean squared logarithmic error.
  
  Examples
  --------
  
  >>> from river import metrics
  
  >>> y_true = [3, -0.5, 2, 7]
  >>> y_pred = [2.5, 0.0, 2, 8]
  
  >>> metric = metrics.RMSLE()
  >>> for yt, yp in zip(y_true, y_pred):
  ...     metric.update(yt, yp)
  
  >>> metric
  RMSLE: 0.357826
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code: def update(self, y_true, y_pred, w=1.0):
      super().update(math.log(y_true + 1), math.log(y_pred + 1), w)
  
file_path: river/river/metrics/mse.py
imports: from __future__ import annotations
  import math
  from river import metrics
label_desc: Use image node_id 1 for calling the RMSLE obj's underlying member method code with example usage: obj.update(y_true, y_pred, w) without return types