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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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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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Nested cross-validation when selecting classifiers is overzealous for most practical applications
Expert Systems With Applications, 2021Jacques Wainer, Gavin Cawley
exaly
Cross validation for model selection: A review with examples from ecology
Ecological Monographs, 2023Luke Yates +2 more
exaly