Results 21 to 30 of about 8,137,182 (304)
A survey of cross-validation procedures for model selection [PDF]
, 2009 Used to estimate the risk of an estimator or to perform model selection, cross-validation is a widespread strategy because of its simplicity and its apparent universality.
Sylvain Arlot, Alain Celisse
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Healthcare Informatics Research, 2021 Objectives With advances in data availability and computing capabilities, artificial intelligence and machine learning technologies have evolved rapidly in recent years. Researchers have taken advantage of these developments in healthcare informatics and
Ilias Tougui, A. Jilbab, J. Mhamdi
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APLIKASI CROSS VALIDATION PADA MODEL SKILL SISWA
Euclid, 2020 One of the activities in the educational test is making a diagnosis to determine whether or not a person's skills are present. This study specifically aims to design student skill models in basic mathematics courses and perform validation using a leave ...
Wahyu Hartono
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Frontiers in Surgery, 2021 Background and Objectives: Total knee arthroplasty (TKA) is widely performed to improve mobility and quality of life for symptomatic knee osteoarthritis patients.
Chang Han +6 more
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PENAKSIRAN FUNGSI DENSITAS TIPE KERNEL DENGAN METODE CROSS-VALIDATION (C-V)
Barekeng, 2007 The choice of the bandwidth h is the main problem of kernel density function. In some situations it might be quite useful to have a set of retes corresponding to different bandwidth.It is necessary to agree which bandwidth is an appropriate one.
Mozart W. Talakua
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Remote Sensing, 2023 Leaf area index (LAI) is a key indicator of vegetation structure and function, and its products have a wide range of applications in vegetation condition assessment and usually act as important input parameters for ecosystem modeling.
Beibei Shen +11 more
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A theory of cross-validation error [PDF]
, 1994 This paper presents a theory of error in cross-validation testing of algorithms for predicting real-valued attributes. The theory justifies the claim that predicting real-valued attributes requires balancing the conflicting demands of simplicity and ...
Turney, Peter D.
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On Estimating Model in Feature Selection With Cross-Validation
IEEE Access, 2019 Both wrapper and hybrid methods in feature selection need the intervention of learning algorithm to train parameters. The preset parameters and dataset are used to construct several sub-optimal models, from which the final model is selected. The question
Chunxia Qi, Jiandong Diao, Like Qiu
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BioMedInformatics, 2023 The COVID-19 virus has made a huge impact on people’s lives ever since the outbreak happened in December 2019. Unfortunately, the COVID-19 virus has not completely vanished from the world yet, and thus, global agitation is still increasing with mutations
Rajkumar Soundrapandiyan +5 more
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Insights into Imaging, 2021 Background Many studies in radiomics are using feature selection methods to identify the most predictive features. At the same time, they employ cross-validation to estimate the performance of the developed models.
A. Demircioğlu
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