Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification-Reference-Cited by-同舟云学术

Non-parametric Bayesian Isotonic Calibration: Fighting Over-Confidence in Binary Classification

Published:2020 Issue: Volume: Page:103-120
ISSN:0302-9743
Container-title:Machine Learning and Knowledge Discovery in Databases
language:
Short-container-title:

Author:

Allikivi Mari-Liis^ORCID,Kull Meelis^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-46147-8_7

Reference21 articles.

1. Banerjee, A., Guo, X., Wang, H.: On the optimality of conditional expectation as a Bregman predictor. IEEE Trans. Inf. Theory 51(7), 2664–2669 (2005)

2. Caruana, R., Niculescu-Mizil, A.: An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 161–168. ACM (2006)

3. DeGroot, M.H., Fienberg, S.E.: The comparison and evaluation of forecasters. Statistician 32, 12–22 (1983)

4. Demšar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7(Jan), 1–30 (2006)

5. Elkan, C.: The foundations of cost-sensitive learning. In: International Joint Conference on Artificial Intelligence, vol. 17, pp. 973–978. Lawrence Erlbaum Associates Ltd (2001)

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction Model of Strong Electromagnetic Effect Phenomenon Based on Complement Naive Bayes;Lecture Notes in Electrical Engineering;2023-12-31

2. Adaptive Calibrator Ensemble: Navigating Test Set Difficulty in Out-of-Distribution Scenarios;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

3. Classifier calibration: a survey on how to assess and improve predicted class probabilities;Machine Learning;2023-05-16

4. Generality-Training of a Classifier for Improved Calibration in Unseen Contexts;Machine Learning and Knowledge Discovery in Databases: Research Track;2023