1. A computer-implemented method for processing a data set containing samples and features, comprising using a computer to perform the following: a first loading step for loading a portion of the samples and each of the features into a database application; a building step for building a feature-selection prediction model using each of the features and a randomly-selected portion of the samples by randomly selecting the samples as they are being loaded in the database application; a definition step for defining useful predictors using the feature-selection prediction model, the useful predictors corresponding to a portion of the features; a second loading step for loading the useful predictors and each of the samples into a database application; and a processing step for determining prediction results by processing the feature-selection prediction model against all of the samples and the portion of the features corresponding to the useful predictors; wherein all of the samples and all of the features of the data set contain too much data to be processed in its entirety by loading all the data set into the database application simultaneously.