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Journal of Mathematical Psychology, 2000
This paper gives a review of cross-validation methods. The original applications in multiple linear regression are considered first. It is shown how predictive accuracy depends on sample size and the number of predictor variables. Both two-sample and single-sample cross-validation indices are investigated. The application of cross-validation methods to
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This paper gives a review of cross-validation methods. The original applications in multiple linear regression are considered first. It is shown how predictive accuracy depends on sample size and the number of predictor variables. Both two-sample and single-sample cross-validation indices are investigated. The application of cross-validation methods to
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Applied Psychological Measurement, 2014
The development of the kernel equating (KE) method enhanced the theory of observed-score equating. In KE, discrete test score distributions are converted into continuous distributions through the use of a Gaussian kernel. Traditionally, the optimal bandwidth for a Gaussian kernel was obtained by minimizing a penalty function.
Tie Liang, Alina A. von Davier
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The development of the kernel equating (KE) method enhanced the theory of observed-score equating. In KE, discrete test score distributions are converted into continuous distributions through the use of a Gaussian kernel. Traditionally, the optimal bandwidth for a Gaussian kernel was obtained by minimizing a penalty function.
Tie Liang, Alina A. von Davier
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Communications in Statistics - Simulation and Computation, 2015
Data-based choice of the bandwidth is an important problem in kernel density estimation. The pseudo-likelihood and the least-squares cross-validation bandwidth selectors are well known, but widely criticized in the literature. For heavy-tailed distributions, the L1 distance between the pseudo-likelihood-based estimator and the density does not seem to ...
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Data-based choice of the bandwidth is an important problem in kernel density estimation. The pseudo-likelihood and the least-squares cross-validation bandwidth selectors are well known, but widely criticized in the literature. For heavy-tailed distributions, the L1 distance between the pseudo-likelihood-based estimator and the density does not seem to ...
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2005
K-fold cross validation is a commonly used technique which takes a set of m examples and partitions them into K equal-size sets (folds) of size m/K. For each set, a classifier is trained on the other sets.
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K-fold cross validation is a commonly used technique which takes a set of m examples and partitions them into K equal-size sets (folds) of size m/K. For each set, a classifier is trained on the other sets.
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Cross‐validation in survival analysis
Statistics in Medicine, 1993AbstractThe predictive value of a statistical model is conceptually different from the explained variation. In this paper we construct a measure of the predictive value of the Cox proportional hazards model, computed from the leave‐one‐out regression coefficients.
P J, Verweij, H C, Van Houwelingen
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No Free Lunch for Cross-Validation
Neural Computation, 1996It is known theoretically that an algorithm cannot be good for an arbitrary prior. We show that in practical terms this also applies to the technique of “cross-validation,” which has been widely regarded as defying this general rule. Numerical examples are analyzed in detail. Their implications to researches on learning algorithms are discussed.
Huaiyu Zhu 0001, Richard Rohwer
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Cross-Validation of the Gordon Siv
Perceptual and Motor Skills, 1968Peer- and self-ratings, and Gordon SIV test scores were obtained from 41 males living in a college dormitory. 5 of 6 validity coefficients between self-ratings and the SIV scores were significantly different from zero, the r for Independence being the exception.
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Asymptotics For and Against Cross-Validation
Biometrika, 1977SUMMARY The asymptotic consistency of cross-validatory assessment and the asymptotic efficiency of cross-validatory choice is investigated both in some generality and also in the context of particular applications.
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Cross-Validation and Variogram Estimation
Theory of Probability & Its Applications, 1993One of the methods used for the interpolation of spatially correlated data is known as kriging, which is a regression technique. Consider a model of the form \(Z(x)\), a random function defined in \(p\)-dimensional space satisfying a weak stationarity condition as follows: \[ \begin{aligned} & E[Z(x + h) - Z(x)] = 0 \text{ for all } x, h;\tag\text{i}\\
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