class_docstr: The objective for optimization during tuning.
  
  Args:
      name: String. The name of the objective.
      direction: String. The value should be "min" or "max" indicating
          whether the objective value should be minimized or maximized.
class_docstr_tok: ["The","objective","for","optimization","during","tuning",".","Args",":","name",":","String",".","The","name","of","the","objective",".","direction",":","String",".","The","value","should","be","``","min","''","or","``","max","''","indicating","whether","the","objective","value","should","be","minimized","or","maximized","."]
docstr: Whether the first objective value is better than the second.
  
  Args:
      a: A float, an objective value to compare.
      b: A float, another objective value to compare.
  
  Returns:
      Boolean, whether the first objective value is better than the
      second.
docstr_tok: ["Whether","the","first","objective","value","is","better","than","the","second",".","Args",":","a",":","A","float",",","an","objective","value","to","compare",".","b",":","A","float",",","another","objective","value","to","compare",".","Returns",":","Boolean",",","whether","the","first","objective","value","is","better","than","the","second","."]
code: def better_than(self, a, b):
      """Whether the first objective value is better than the second.
  
      Args:
          a: A float, an objective value to compare.
          b: A float, another objective value to compare.
  
      Returns:
          Boolean, whether the first objective value is better than the
          second.
      """
      return (a > b and self.direction == "max") or (
          a < b and self.direction == "min"
      )
  
imports: from keras_tuner.api_export import keras_tuner_export
  from keras_tuner.engine import metrics_tracking
label_desc: Use image node_id 4 for calling the Objective obj's underlying member method code with example usage: obj.better_than(a, b) and returns: unknown