Results 1 to 10 of about 4,483,884 (302)
Cross-Validation Visualized: A Narrative Guide to Advanced Methods
Machine Learning and Knowledge ExtractionThis study delves into the multifaceted nature of cross-validation (CV) techniques in machine learning model evaluation and selection, underscoring the challenge of choosing the most appropriate method due to the plethora of available variants.
Johannes Allgaier, Rüdiger Pryss
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Cross-Validation Without Doing Cross-Validation in Genome-Enabled Prediction
G3: Genes, Genomes, Genetics, 2016 Cross-validation of methods is an essential component of genome-enabled prediction of complex traits. We develop formulae for computing the predictions that would be obtained when one or several cases are removed in the training process, to become ...
Daniel Gianola, Chris-Carolin Schön
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Bernoulli, 2023 In many applications, we have access to the complete dataset but are only interested in the prediction of a particular region of predictor variables. A standard approach is to find the globally best modeling method from a set of candidate methods. However, it is perhaps rare in reality that one candidate method is uniformly better than the others.
Jiawei Zhang 0007 +2 more
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Missing value imputation using least squares techniques in contaminated matrices
MethodsX, 2022 This paper describes strategies to reduce the possible effect of outliers on the quality of imputations produced by a method that uses a mixture of two least squares techniques: regression and lower rank approximation of a matrix.
Marisol Garcia-Peña +2 more
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Applied Sciences, 2020 The leave-one-out cross validation (LOO-CV), which is a model-independent evaluate method, cannot always select the best of several models when the sample size is small.
Liye Lv, Xueguan Song, Wei Sun
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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 0018 +4 more
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Computer simulation of Cerebral Arteriovenous Malformation—validation analysis of hemodynamics parameters [PDF]
PeerJ, 2017 Problem The purpose of this work is to provide some validation methods for evaluating the hemodynamic assessment of Cerebral Arteriovenous Malformation (CAVM).
Y. Kiran Kumar +2 more
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The Problem of Measurement Equivalence or Invariance in Instruments
International Journal of Assessment Tools in Education, 2021 The purpose of this study is to discuss the validity of equivalence in the sample groups of young and adult; females and males in the scale of assessing the attitudes towards foreign language skills and to offer the researchers that will use this scale ...
Tülin (otbiçer) Acar
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Comprehensive validation of silicon cross sections
Nuclear Engineering and Technology, 2020 Silicon, especially silicon in the form of SiO2, is a major component of rocks. Final spent fuel storages, which are being designed, are located in suitable rock formations in the Earth's crust.
Tomáš Czakoj +5 more
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The generalized cross validation filter [PDF]
Automatica, 2018 Generalized cross validation (GCV) is one of the most important approaches used to estimate parameters in the context of inverse problems and regularization techniques. A notable example is the determination of the smoothness parameter in splines. When the data are generated by a state space model, like in the spline case, efficient algorithms are ...
Bottegal, Giulio, Pillonetto, Gianluigi
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