A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methods
@article{Burman1989ACS, title={A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methods}, author={Prabir Burman}, journal={Biometrika}, year={1989}, volume={76}, pages={503-514}, url={https://api.semanticscholar.org/CorpusID:16701030} }
Concepts of v-fold cross-validation and repeated learning-testing methods are introduced here and are computationally much less expensive than ordinary cross- validation and can be used in its place in many problems.
675 Citations
Some Issues in Cross-Validation
- 1991
Mathematics, Computer Science
A new type of cross- validation is proposed here for model selection problems when the data is generated by a stationary process, which is an off-shoot of both ordinary cross-validation and v-fold cross- validation.
An assessment of ten-fold and Monte Carlo cross validations for time series forecasting
- 2013
Computer Science, Mathematics
Experimental results, using time series of the NN3 tournament, found that Monte Carlo cross validation is more stable than ten-fold cross validation for selecting the best forecasting model.
Multiple predicting K-fold cross-validation for model selection
- 2018
Computer Science, Mathematics
This study proposes a new CV method that uses folds of the data for model validation, while the other fold is for model construction, and provides predicted values for each observation to reduce variation in the assessment due to the averaging.
Estimation of prediction error by using K-fold cross-validation
- 2011
Computer Science, Mathematics
This paper investigates two families that connect the training error and K-fold cross-validation, which has a downward bias and has an upward bias.
A survey of cross-validation procedures for model selection
- 2010
Mathematics
This survey intends to relate the model selection performances of cross-validation procedures to the most recent advances of model selection theory, with a particular emphasis on distinguishing empirical statements from rigorous theoretical results.
Consistent Cross Validation with Stable Learners
- 2022
Computer Science, Mathematics
A debiased version of the K-fold is proposed which is consistent for any uniformly stable learner and applies to the problem of model selection and demonstrates empirically the usefulness of the promoted approach on real world datasets.
Cross-validation
- 2017
Mathematics
This text is a survey on cross-validation. We define all classical cross-validation procedures, and we study their properties for two different goals: estimating the risk of a given estimator, and…
On optimal data split for generalization estimation and model selection
- 1999
Computer Science, Mathematics
The theoretical basics of various cross-validation techniques are described with the purpose of reliably estimating the generalization error and optimizing the model structure for reliably estimating a single location parameter.
An empirical comparison of $$V$$V-fold penalisation and cross-validation for model selection in distribution-free regression
- 2014
Computer Science, Mathematics
Cases in which VFCV and $$V$$V-fold penalisation provide poor estimates of the risk, respectively, are highlighted, and a modified penalisation technique is introduced to reduce the estimation error.
13 References
An alternative method of cross-validation for the smoothing of density estimates
- 1984
Mathematics
An alternative method of cross-validation, based on integrated squared error, recently also proposed by Rudemo (1982), is derived, and Hall (1983) has established the consistency and asymptotic optimality of the new method.
Cross‐Validatory Choice and Assessment of Statistical Predictions
- 1974
Mathematics
SUMMARY A generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription. The examples used to illustrate…
The Predictive Sample Reuse Method with Applications
- 1975
Mathematics
A recently devised method of prediction based on sample reuse techniques that is most useful in low structure data paradigms that involve minimal assumptions is presented.
Classification and regression trees
- 1983
Computer Science, Mathematics
This chapter discusses tree classification in the context of medicine, where right Sized Trees and Honest Estimates are considered and Bayes Rules and Partitions are used as guides to optimal pruning.
Generalized $L-, M-$, and $R$-Statistics
- 1984
Mathematics
Abstract : A class of statisticss generalizing U-statistics and L-statistics, and containing other varieties of statistics as well, such as trimmed U-statistics, is studied. Using the differentiable…
Estimating Optimal Transformations for Multiple Regression and Correlation.
- 1985
Mathematics
Abstract In regression analysis the response variable Y and the predictor variables X 1 …, Xp are often replaced by functions θ(Y) and O1(X 1), …, O p (Xp ). We discuss a procedure for estimating…
Optimal Bandwidth Selection in Nonparametric Regression Function Estimation
- 1985
Mathematics
On considere des estimateurs du noyau d'une fonction de regression multivariable et une regle de selection selon la largeur de bande formulee en terme de validation croisee
Jackknife Approximations to Bootstrap Estimates
- 1984
Mathematics
Let T be an estimate of the form Tn = T(F ) where F is the nn n' n sample cdf of n iid observations and T is a locally quadratic functional defined on cdf's. Then, the normalized jackknife estimates…
Approximation Theorems of Mathematical Statistics
- 1980
Mathematics
Preliminary Tools and Foundations. The Basic Sample Statistics. Transformations of Given Statistics. Asymptotic Theory in Parametric Inference. U--Statistics. Von Mises Differentiable Statistical…