class_docstr: Layer to calibrate the model outputs.
  
  The class implements the heuristics described in :cite:`calibration`,
  using Platt scaling :cite:`platt1999probabilistic`.
  
  See the docs of :meth:`~ampligraph.latent_features.models.ScoringBasedEmbeddingModel.calibrate()` for more details.
code: def get_config(self):
      config = super(CalibrationLayer, self).get_config()
      config.update(
          {
              "pos_size": self.pos_size,
              "neg_size": self.neg_size,
              "positive_base_rate": self.positive_base_rate,
          }
      )
      return config
  
imports: import tensorflow
label_desc: Use image node_id 1 for calling the CalibrationLayer obj's underlying member method code with example usage: obj.get_config() and returns: config