class_docstr: An object to represent a (prediction) interval.
  
  Users are not expected to use this class as-is. Instead, they should use the `with_interval`
  parameter of the `predict_one` method of any regressor or classifier wrapped with a conformal
  prediction method.
  
  Parameters
  ----------
  lower
      The lower bound of the interval.
  upper
      The upper bound of the interval.
class_docstr_tok: ["An","object","to","represent","a","(","prediction",")","interval",".","Users","are","not","expected","to","use","this","class","as-is",".","Instead",",","they","should","use","the","`","with_interval","`","parameter","of","the","`","predict_one","`","method","of","any","regressor","or","classifier","wrapped","with","a","conformal","prediction","method",".","Parameters","--","--","--","--","--","lower","The","lower","bound","of","the","interval",".","upper","The","upper","bound","of","the","interval","."]
docstr: The width of the interval.
docstr_tok: ["The","width","of","the","interval","."]
code: def width(self):
      """The width of the interval."""
      return self.upper - self.lower
  
imports: from __future__ import annotations
  import dataclasses
label_desc: Use image node_id 2 for calling the Interval obj's underlying member method code with example usage: obj.width() and returns: unknown