Establishment of Best Practices for Evidence for Prediction: A Review.
Sign Up to like & getrecommendations! Published in 2019 at "JAMA psychiatry"
DOI: 10.1001/jamapsychiatry.2019.3671
Abstract: Importance Great interest exists in identifying methods to predict neuropsychiatric disease states and treatment outcomes from high-dimensional data, including neuroimaging and genomics data. The goal of this review is to highlight several potential problems that… read more here.
Keywords: evidence prediction; cross validation; evidence; best practices ... See more keywords
Using functional traits to predict species growth trajectories, and cross‐validation to evaluate these models for ecological prediction
Sign Up to like & getrecommendations! Published in 2019 at "Ecology and Evolution"
DOI: 10.1002/ece3.4693
Abstract: Abstract Modeling plant growth using functional traits is important for understanding the mechanisms that underpin growth and for predicting new situations. We use three data sets on plant height over time and two validation methods—in‐sample… read more here.
Keywords: cross validation; using functional; functional traits; model ... See more keywords
Genome-wide association studies combined with k-fold cross-validation identify rs17822931 as an ancestry-informative marker in Han Chinese population.
Sign Up to like & getrecommendations! Published in 2023 at "Electrophoresis"
DOI: 10.1002/elps.202200227
Abstract: DNA-based ancestry inference has long been a research hot spot in forensic science. The differentiation of Han Chinese population, such as the northern-to-southern substructure, would benefit forensic practice. In the present study, we enrolled participants… read more here.
Keywords: cross validation; chinese population; fold cross; han chinese ... See more keywords
Detecting association of rare and common variants based on cross‐validation prediction error
Sign Up to like & getrecommendations! Published in 2017 at "Genetic Epidemiology"
DOI: 10.1002/gepi.22034
Abstract: Despite the extensive discovery of disease‐associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants may explain additional disease risk or trait variability. Although sequencing technology provides a supreme opportunity… read more here.
Keywords: based cross; cross validation; common variants; association rare ... See more keywords
Estimates for the generalized cross-validation function via an extrapolation and statistical approach
Sign Up to like & getrecommendations! Published in 2018 at "Calcolo"
DOI: 10.1007/s10092-018-0266-3
Abstract: Generalized cross-validation (GCV) is a popular tool for specifying the tuning parameter in linear regression model or equivalently the regularization parameter in Tikhonov regularization. In this work, we are concerned with the estimation and minimization… read more here.
Keywords: function; generalized cross; cross validation; statistical approach ... See more keywords
CV-α: designing validations sets to increase the precision and enable multiple comparison tests in genomic prediction
Sign Up to like & getrecommendations! Published in 2021 at "Euphytica"
DOI: 10.1007/s10681-021-02831-x
Abstract: Usually, the comparison among genomic prediction models is based on validation schemes as Repeated Random Subsampling (RRS) or K-fold cross-validation. Nevertheless, the design of training and validation sets has a high effect on the way… read more here.
Keywords: comparison; genomic prediction; methodology; validation ... See more keywords
Conditional vs marginal estimation of the predictive loss of hierarchical models using WAIC and cross-validation
Sign Up to like & getrecommendations! Published in 2018 at "Statistics and Computing"
DOI: 10.1007/s11222-017-9736-8
Abstract: The predictive loss of Bayesian models can be estimated using a sample from the full-data posterior by evaluating the Watanabe-Akaike information criterion (WAIC) or using an importance sampling (ISCVL) approximation to leave-one-out cross-validation loss. With… read more here.
Keywords: cross validation; level; conditional level; predictive loss ... See more keywords
Imaging HDACs In Vivo: Cross-Validation of the [11C]Martinostat Radioligand in the Pig Brain
Sign Up to like & getrecommendations! Published in 2019 at "Molecular Imaging and Biology"
DOI: 10.1007/s11307-019-01403-9
Abstract: PurposeWith the emerging knowledge about the impact of epigenetic alterations on behavior and brain disorders, the ability to measure epigenetic alterations in brain tissue in vivo has become critically important. We present the first in… read more here.
Keywords: cross validation; pig brain; protein levels; brain ... See more keywords
Discriminant analysis and feature selection in mass spectrometry imaging using constrained repeated random sampling - Cross validation (CORRS-CV).
Sign Up to like & getrecommendations! Published in 2020 at "Analytica chimica acta"
DOI: 10.1016/j.aca.2019.10.039
Abstract: The identification of biomarkers through Mass spectrometry imaging (MSI) is gaining popularity in the clinical field. However, considering the complexity of spectral and spatial variables faced, data mining of the hyperspectral images can be troublesome.… read more here.
Keywords: validation; mass spectrometry; cross validation; corrs ... See more keywords
FBSED based automatic diagnosis of COVID-19 using X-ray and CT images
Sign Up to like & getrecommendations! Published in 2021 at "Computers in Biology and Medicine"
DOI: 10.1016/j.compbiomed.2021.104454
Abstract: This work introduces the Fourier-Bessel series expansion-based decomposition (FBSED) method, which is an implementation of the wavelet packet decomposition approach in the Fourier-Bessel series expansion domain. The proposed method has been used for the diagnosis… read more here.
Keywords: covid using; fbsed based; cross validation; diagnosis ... See more keywords
Asymptotic Properties of Generalized Cross Validation Estimators for Regularized System Identification
Sign Up to like & getrecommendations! Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.09.130
Abstract: Abstract In this paper, we study the asymptotic properties of the generalized cross validation (GCV) hyperparameter estimator and establish its connection with the Stein’s unbiased risk estimators (SURE) as well as the mean squared error… read more here.
Keywords: properties generalized; generalized cross; cross validation; asymptotic properties ... See more keywords