Results 31 to 40 of about 1,327,683 (276)
Multifidelity Cross-Validation
AIAA AVIATION FORUM AND ASCEND 2024arXiv admin note: text overlap with arXiv:2203 ...
Renganathan, S. Ashwin, Carlson, Kade
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Possibly Nonstationary Cross-Validation [PDF]
SSRN Electronic Journal, 2016 Cross-validation is the most common data-driven procedure for choosing smoothing parameters in nonparametric regression. For the case of kernel estimators with iid or strong mixing data, it is well-known that the bandwidth chosen by cross-validation is optimal with respect to the average squared error and other performance measures.
Bandi, Federico M +2 more
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JTAM (Jurnal Teori dan Aplikasi Matematika), 2022 Grade point average (GPA) is initial information for supervisors to characterize their supervised students. One model that can be used to predict a student's study period based on GPA is a machine learning-based regression model so that supervisors can ...
Sri Nurdiati, Mohamad Khoirun Najib
doaj +1 more source
Controlling the Overfitting of Heritability in Genomic Selection through Cross Validation. [PDF]
, 2017 In genomic selection (GS), all the markers across the entire genome are used to conduct marker-assisted selection such that each quantitative trait locus of complex trait is in linkage disequilibrium with at least one marker.
Jia, Zhenyu
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Validation of MCMC-Based Travel Simulation Framework Using Mobile Phone Data
Frontiers in Future Transportation, 2021 An essential step in agent-based travel demand models is the characterization of the population, including transport-related attributes. This study looks deep into various mobility data in the province of Liège, Belgium.
Suxia Gong +7 more
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A bias correction for the minimum error rate in cross-validation
, 2009 Tuning parameters in supervised learning problems are often estimated by cross-validation. The minimum value of the cross-validation error can be biased downward as an estimate of the test error at that same value of the tuning parameter.
Tibshirani, Robert, Tibshirani, Ryan J.
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Concentration inequalities of the cross-validation estimate for stable predictors [PDF]
, 2010 In this article, we derive concentration inequalities for the cross-validation estimate of the generalization error for stable predictors in the context of risk assessment.
Cornec, Matthieu
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Nurses are central to cancer care for children and adolescents, yet no comprehensive synthesis has defined essential core competencies for pediatric oncology nursing (PON) practice internationally, particularly in Latin America and the Caribbean (LAC).
Luís Carlos Lopes‐Júnior +7 more
wiley +1 more source
Usefulness of accounting information vs. market information in bankruptcy Prediction [PDF]
مجله دانش حسابداری, 2012 The usefulness of accounting information has always been source of concern for standard setters that view the main goal of financial reporting as the issue required for generating useful information to facilitate decision making process according to ...
Gholamreza Karami +1 more
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Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Cross-validation (CV) is the most widely adopted approach for selecting the optimal model. However, the computation of CV has high complexity due to multiple times of learner training, making it disabled for large scale model selection. In this paper, we present an approximate approach to CV based on the theoretical notion of Bouligand influence ...
Yong Liu +4 more
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