1. A method of classifying items, comprising: (a) obtaining initial feature sets for a current batch of items; (b) generating classification predictions for the items based on the initial feature sets for the items, using a set of existing classifiers; (c) appending the classification predictions as additional features to the respective feature sets of the items, thereby obtaining enhanced feature sets; (d) training a first classifier, using a plurality of the items as training samples and using the enhanced feature sets of the training samples; and (e) classifying items in the current batch using the enhanced feature sets of the items and the first classifier, wherein at least one of the existing classifiers was trained on a different set of items that are representative of a corresponding different time, and wherein steps (a)-(e) are executed by one or more computers.