Results 11 to 20 of about 4,483,884 (302)
Procrustes Cross-Validation — a Bridge Between Cross-Validation and Independent Validation Set [PDF]
Analytical Chemistry, 2020 In this paper, we propose a new approach for validation of chemometric models. It is based on k-fold cross-validation algorithm, but in contrast to conventional cross-validation, our approach makes it possible to create a new dataset, which carries sampling uncertainty estimated by the cross-validation procedure.
Sergey Kucheryavskiy +3 more
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Cross-Validation With Confidence [PDF]
Journal of the American Statistical Association, 2019 Cross-validation is one of the most popular model selection methods in statistics and machine learning. Despite its wide applicability, traditional cross validation methods tend to select overfitting models, due to the ignorance of the uncertainty in the testing sample. We develop a new, statistically principled inference tool based on cross-validation
Jing Lei (682227)
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Balanced Leave-One-Subject-Out Cross- Validation for Microsleep Classification
Current Directions in Biomedical Engineering, 2021 Inter-individual differences in the feature distribution of electroencephalograms (EEG) during microsleep (MS) raise questions about the generalizability of the methodology, because methodology should have the same validity for subjects to be included in
Pauli Martin Patrick +2 more
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Spatial Regression Models for Field Trials: A Comparative Study and New Ideas
Frontiers in Plant Science, 2022 Naturally occurring variability within a study region harbors valuable information on relationships between biological variables. Yet, spatial patterns within these study areas, e.g., in field trials, violate the assumption of independence of ...
Stijn Hawinkel +5 more
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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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ercbk/nested-cross-validation-comparison: v1.0
, 2021 Experimenting with various implementations and methods of nested cross-validation in R and ...
Eric Book
core +1 more source
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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