A method for estimating the accuracy (or error) of an inducer by dividing the data into k mutually exclusive subsets (the ``folds'') of approximately equal size. The inducer is trained and t [..]

When using data with an algorithm, “the name given to a set of techniques that divide up data into training sets and test sets. The training set is given to the algorithm, along with the correct answe [..]

A technique to assess the generalization of the constructed model by the analysis of accuracy of the model predictions on presumably independent dataset.

noun. A model-evaluation technique wherein the legitimacy of a design is examined by rendered new information upon it.

A process for validating the results of a predictive model by using an independent dataset.

A way of choosing the window width for a kernel estimation. The method is to select, from a set of possible window widths, one that minimizes the sum of errors made in predicting each data point by us [..]

(statistics) Any technique or instance of assessing how the results of a statistical analysis will generalize to an independent dataset.

Cross-validation refers to the process of assessing the predictive accuracy of a model in a test sample (sometimes also called a cross-validation sample) relative to its predictive accuracy in the lea [..]