Figure 1.

Summary of the notation and basic procedure used throughout this article. The training dataset, D, is repeatedly subsampled to obtain a collection of datasets, ${\left\{D_k\right\}}_{k=1}^K,$ and left-out datasets, ${\left\{D_{\backslash k}\right\}}_{k=1}^K.$ For k = 1, … , K, a predictive model is trained on D_k and then used to predict the class labels of the observations in D_\k, yielding a selected set of size m, s_mk, and a correct classification rate, c_mk.