A method for comparing two or more conjectured variogram (or covariance) models. The technique depends on Jackknifing the data and on the exactness of the kriging estimator.
A method for estimating the accuracy (or error) of an inducer by dividing the data into mutually exclusive subsets (the ``folds'') of approximately equal size. The inducer is trained and tested times. Each time it is trained on the data set minus a fold and tested on that fold. The accuracy estimate is the average accuracy for the folds.
fold. The data set is divided equally into k randomly selected, mutually exclusive subsets called folds. k- 1 networks are trained sequentially on all combinations of k- 1 folds, while the performance of the trained networks is tested on the one remaining folds. The average of k- 1 such errors is an estimate of the generalisation performance metric.
A technique for evaluating the accuracy of a classification or regression model. This technique is used when there are insufficient cases for using separate sets of data for model building and testing. The data table is divided into several parts, with each part in turn being used to evaluate a model built using the remaining parts. Cross-validation occurs automatically for Naive Bayes and Adaptive Bayes Networks. Available in the Java interface only.
is a re-sampling technique used in forecast verification when independent data for forecast testing are limited. Cross-validation repeatedly divides all available data into development and verification data subsets. It evaluates performance of a forecast algorithm on the development subset and uses the verification subset as an independent sample [pg 194-195, 3] Top A-C D-H I-M N-R S-Z
A statistical method for estimating prediction error.
A method of estimating predictive error. Cross validation splits that dataset into k equal-sized pieces called folds (typically 10). k predictive models are built, each tested on a distinct fold after being trained on the remaining folds. The process can be repeated multiple times to increase the reliability of the estimate.
Cross-validation, sometimes called rotation estimation(Morgan Kaufmann, San Mateo) Chang, J., Luo, Y., and Su, K. 1992. GPSM: a Generaized Probabilistic Semantic Model for ambiguity resolution. In Proceedings of the 30th Annual Meeting on Association For Computational Linguistics (Newark, Delaware, June 28 - July 02, 1992).