Results 11 to 20 of about 1,327,683 (276)
Monte Carlo cross-validation for a study with binary outcome and limited sample size
BMC Medical Informatics and Decision Making, 2022 Cross-validation (CV) is a resampling approach to evaluate machine learning models when sample size is limited. The number of all possible combinations of folds for the training data, known as CV rounds, are often very small in leave-one-out CV ...
Guogen Shan
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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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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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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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Neural network model of the wells' drilling speed and modes predicting in complex reservoirs
Известия высших учебных заведений: Нефть и газ, 2021 The article considers the problem connected with the study of well drilling rates in complex reservoirs. Its solution is presented in the form of a neural network model that takes into account the structural, geomechanical and technological features of ...
Yu. E. Katanov
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Estimating misclassification error: a closer look at cross-validation based methods
BMC Research Notes, 2012 Background To estimate a classifier’s error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV) methods based on sampling without replacement.
Ounpraseuth Songthip +3 more
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Cross-validation in nonparametric regression with outliers [PDF]
, 2005 A popular data-driven method for choosing the bandwidth in standard kernel regression is cross-validation. Even when there are outliers in the data, robust kernel regression can be used to estimate the unknown regression curve [Robust and Nonlinear Time ...
Leung, Denis Heng-Yan
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Plants, 2023 A large amount of data on various traits is accumulated over the course of a breeding program and can be used to optimize various aspects of the crop improvement pipeline. We leveraged data from advanced yield trials (AYT) of three classes of peas (green,
Sintayehu D. Daba +2 more
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A Comparison of Forecasting Mortality Models Using Resampling Methods
Mathematics, 2020 The accuracy of the predictions of age-specific probabilities of death is an essential objective for the insurance industry since it dramatically affects the proper valuation of their products.
David Atance, Ana Debón, Eliseo Navarro
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Assessing behavioural changes in ALS: cross-validation of ALS-specific measures [PDF]
, 2017 Objective: The Beaumont Behavioural Inventory (BBI) is a behavioural proxy report for the assessment of behavioural changes in ALS. This tool has been validated against the FrSBe, a non-ALS specific behavioural assessment, and further comparison of the ...
BR Brooks +16 more
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