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Conformal and Probabilistic Prediction with Applications [electronic resource] : 5th International Symposium, COPA 2016, Madrid, Spain, April 20-22, 2016, Proceedings / edited by Alexander Gammerman, Zhiyuan Luo, Jesús Vega, Vladimir Vovk.

Contributor(s): Gammerman, Alexander [editor.] | Luo, Zhiyuan [editor.] | Vega, Jesús [editor.] | Vovk, Vladimir [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 9653Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XII, 229 p. 45 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319333953.Subject(s): Artificial intelligence | Algorithms | Application software | Data mining | Database management | Computer science | Artificial Intelligence | Algorithms | Computer and Information Systems Applications | Data Mining and Knowledge Discovery | Database Management | Theory of ComputationAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Theory of conformal prediction -- Applications of conformal prediction -- Machine learning.
In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in Madrid, Spain, in April 2016. The 14 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 23 submissions and cover topics on theory of conformal prediction; applications of conformal prediction; and machine learning.
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Theory of conformal prediction -- Applications of conformal prediction -- Machine learning.

This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in Madrid, Spain, in April 2016. The 14 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 23 submissions and cover topics on theory of conformal prediction; applications of conformal prediction; and machine learning.

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