Criteria of Efficiency for Conformal Prediction

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• 关键词：Conformal prediction ; Predictive efficiency ; Informational efficiency
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9653
• 期：1
• 页码：23-39
• 全文大小：312 KB
• 参考文献：1.Balasubramanian, V.N., Ho, S.S., Vovk, V. (eds.): Conformal Prediction for Reliable Machine Learning: Theory, Adaptations, and Applications. Elsevier, Amsterdam (2014)
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  3.Fedorova, V., Gammerman, A., Nouretdinov, I., Vovk, V.: Conformal prediction under hypergraphical models. In: Papadopoulos, H., Andreou, A.S., Iliadis, L., Maglogiannis, I. (eds.) AIAI 2013. IFIP AICT, vol. 412, pp. 371–383. Springer, Heidelberg (2013)CrossRef
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  6.Le Cun, Y., Boser, B.E., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, W.E., Jackel, L.D.: Handwritten digit recognition with a back-propagation network. In: Touretzky, D.S. (ed.) Advances in Neural Information Processing Systems 2, pp. 396–404. Morgan Kaufmann, San Francisco, CA (1990)
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  10.Melluish, T., Saunders, C., Nouretdinov, I., Vovk, V.: Comparing the Bayes and typicalness frameworks. In: Flach, P.A., De Raedt, L. (eds.) ECML 2001. LNCS (LNAI), vol. 2167, pp. 360–371. Springer, Heidelberg (2001)CrossRef
  11.Papadopoulos, H., Gammerman, A., Vovk, V.: Special issue of the conformal prediction and its applications. Ann. Math. Artif. Intell. 74(1–2), 1–7 (2015). SpringerMathSciNet CrossRef MATH
  12.Saunders, C., Gammerman, A., Vovk, V.: Transduction with confidence and credibility. In: Dean, T. (ed.) Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, vol. 2, pp. 722–726. Morgan Kaufmann, San Francisco, CA (1999)
  13.Smith, J., Nouretdinov, I., Craddock, R., Offer, C., Gammerman, A.: Anomaly detection of trajectories with kernel density estimation by conformal prediction. In: Iliadis, L., Maglogiannis, I., Papadopoulos, H., Sioutas, S., Makris, C. (eds.) Artificial Intelligence Applications and Innovations. IFIP AICT, vol. 437, pp. 271–280. Springer, Heidelberg (2014)
  14.Vovk, V., Gammerman, A., Shafer, G.: Algorithmic Learning in a Random World. Springer, New York (2005)MATH
  15.Vovk, V., Petej, I., Fedorova, V.: From conformal to probabilistic prediction. In: Iliadis, L., Maglogiannis, I., Papadopoulos, H., Sioutas, S., Makris, C. (eds.) Artificial Intelligence Applications and Innovations. IFIP AICT, vol. 437, pp. 221–230. Springer, Heidelberg (2014)
  
• 作者单位：Vladimir Vovk (17)
  Valentina Fedorova (18)
  Ilia Nouretdinov (17)
  Alexander Gammerman (17)
  
  17. Computer Learning Research Centre, Royal Holloway, University of London, Egham, Surrey, UK
  18. Yandex, Moscow, Russia
  
• 丛书名：Conformal and Probabilistic Prediction with Applications
• ISBN：978-3-319-33395-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9653

文摘

We study optimal conformity measures for various criteria of efficiency in an idealised setting. This leads to an important class of criteria of efficiency that we call probabilistic; it turns out that the most standard criteria of efficiency used in literature on conformal prediction are not probabilistic.