Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how...

Look up cross-validation in Wiktionary, the free dictionary. Cross-validation may refer to: Cross-validation (statistics), a technique for estimating the...

in training (for example in cross-validation), the test data set is also called a holdout data set. The term "validation set" is sometimes used instead...

Purged cross-validation is a variant of k-fold cross-validation designed to prevent look-ahead bias in time series and other structured data, developed...

the validation set. Averaging the quality of the predictions across the validation sets yields an overall measure of prediction accuracy. Cross-validation...

Look up validation or validate in Wiktionary, the free dictionary. Validation may refer to: Data validation, in computer science, ensuring that data inserted...

the residual plots may indicate a flaw in the model. Cross validation is a method of model validation that iteratively refits the model, each time leaving...

In computing, data validation or input validation is the process of ensuring data has undergone data cleansing to confirm it has data quality, that is...

model via AIC, it is usually good practice to validate the absolute quality of the model. Such validation commonly includes checks of the model's residuals...

Generalized Cross-Validation (GCV), a minor variant on the Akaike information criterion that approximates the leave-one-out cross-validation score in the...

OOB error stabilizes, it will converge to the cross-validation (specifically leave-one-out cross-validation) error. The advantage of the OOB method is that...

assessed. The cross-validation can be categorized as either method validation or analytical data validation.[citation needed] Validation (drug manufacture)...

For validation of QSAR models, usually various strategies are adopted: internal validation or cross-validation (actually, while extracting data, cross validation...

at the correct number of clusters. One can also use the process of cross-validation to analyze the number of clusters. In this process, the data is partitioned...

performance metric, typically measured by cross-validation on the training set or evaluation on a hold-out validation set. Since the parameter space of a machine...

be generalized beyond normal distributions, by using leave-one out cross validation: a r g m i n h J ^ ( h ) = a r g m i n h ( 2 ( n − 1 ) h − n + 1 n...

converges in probability to HAMISE. Smoothed cross validation (SCV) is a subset of a larger class of cross validation techniques. The SCV estimator differs from...

leave-one-out cross-validation stability, says that to be stable, the prediction error for each data point when leave-one-out cross validation is used must...

exhaustive form of cross-validation, as it tests all the possible ways that the original data can be divided into a training and a validation set. Instead of...

such as cross-validation, perform better on average on practical problems (when compared with random choice or with anti-cross-validation). However...

statistics is the use of out-of-sample cross validation techniques in meta-analysis. It forms the basis of the validation statistic, Vn, which is used to test...

In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This...

Premature featurization; leaking from premature featurization before Cross-validation/Train/Test split (must fit MinMax/ngrams/etc on only the train split...

using cross-validation to select the best model from a bucket of models. Likewise, the results from BMC may be approximated by using cross-validation to...

words "verification" and "validation" are sometimes preceded with "independent", indicating that the verification and validation is to be performed by a...

examples. Cross-validation is a more sophisticated version of training a test set. For cross-sectional data, one approach to cross-validation works as...

In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling. It is especially useful...

patches to be validated. Compiler correctness Cross-validation Formal verification Functional specification Independent Verification and Validation Facility...

Minimum cross-validation error: when trying to choose among hypotheses, select the hypothesis with the lowest cross-validation error. Although cross-validation...

Statistical learning theory Boosting (machine learning) Cross-validation, in particular using a "validation set" Neural networks Girosi, Federico; Michael Jones;...