Obtaining Well Calibrated Probabilities Using Bayesian Binning

  title={Obtaining Well Calibrated Probabilities Using Bayesian Binning},
  author={Mahdi Pakdaman Naeini and Gregory F. Cooper and Milos Hauskrecht},
  journal={Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence},
Learning probabilistic predictive models that are well calibrated is critical for many prediction and decision-making tasks in artificial intelligence. In this paper we present a new non-parametric calibration method called Bayesian Binning into Quantiles (BBQ) which addresses key limitations of existing calibration methods. The method post processes the output of a binary classification algorithm; thus, it can be readily combined with many existing classification algorithms. The method is… CONTINUE READING
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