class_docstr: Stop the optimization if the `n_best` minima are within `delta`
  
  Stop the optimizer if the absolute difference between the `n_best`
  objective values is less than `delta`.
class_docstr_tok: ["Stop","the","optimization","if","the","`","n_best","`","minima","are","within","`","delta","`","Stop","the","optimizer","if","the","absolute","difference","between","the","`","n_best","`","objective","values","is","less","than","`","delta","`","."]
code: def __init__(self, delta, n_best=5):
      super(EarlyStopper, self).__init__()
      self.delta = delta
      self.n_best = n_best
  
imports: from time import time
  import numpy
  from skopt.utils import dump
label_desc: Use image node_id 1 to create a new DeltaYStopper object from inherited base classes: EarlyStopper with example: obj = DeltaYStopper(delta, n_best)