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Titlebook: Conformal and Probabilistic Prediction with Applications; 5th International Sy Alexander Gammerman,Zhiyuan Luo,Vladimir Vovk Conference pro

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书目名称Conformal and Probabilistic Prediction with Applications
副标题5th International Sy
编辑Alexander Gammerman,Zhiyuan Luo,Vladimir Vovk
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Conformal and Probabilistic Prediction with Applications; 5th International Sy Alexander Gammerman,Zhiyuan Luo,Vladimir Vovk Conference pro
描述.This book constitutes the refereed proceedings of the 5th InternationalSymposium on Conformal and Probabilistic Prediction with Applications, COPA2016, held in Madrid, Spain, in April 2016...The 14 revised fullpapers presented together with 1 invited paper were carefully reviewed andselected from 23 submissions and cover topics on theory of conformal prediction; applicationsof conformal prediction; and machine learning..
出版日期Conference proceedings 2016
关键词big data applications; data mining; machine learning; pattern recognition; universal prediction; active l
版次1
doihttps://doi.org/10.1007/978-3-319-33395-3
isbn_softcover978-3-319-33394-6
isbn_ebook978-3-319-33395-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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https://doi.org/10.1057/9781137355560diction of a high fidelity function at some point, we can update the surrogate model with the low fidelity function value at this point. So, we avoid issues related to the inversion of large covariance matrices — as we can construct model using only a moderate low fidelity sample size. We applied de
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Joint Prediction of Chronic Conditions Onset: Comparing Multivariate Probits with Multiclass Support that MSVMs predictions have specificity rates similar to those of MVPs, but sensitivity rates that are on average 12 % points larger than those of MVPs, translating in a large average improvement in sensitivity of 30 %.
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https://doi.org/10.1007/978-3-319-33395-3big data applications; data mining; machine learning; pattern recognition; universal prediction; active l
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978-3-319-33394-6Springer International Publishing Switzerland 2016
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