class_docstr: This class handles specific types of batch evaluators, based on the sampling of anchor points (examples are random and Thompson sampling).
code: def __init__(self, acquisition, batch_size, **kwargs):
      self.acquisition = acquisition
      self.batch_size = batch_size
      self.space = acquisition.space
      # The following number of anchor points is heuristically picked, to obtain good and various batches
      self.num_anchor = 5 * batch_size
  
file_path: GPyOpt/GPyOpt/core/evaluators/base.py
imports: import numpy
label_desc: Use image node_id 1 to create a new SamplingBasedBatchEvaluator object from inherited base classes: EvaluatorBase with example: obj = SamplingBasedBatchEvaluator(acquisition, batch_size)