1. A computerized method for supervised learning, comprising: receiving a set of training elements; selecting a basis element from the set of training elements; adding the basis element to a basis element set; conducting an optimization test on the basis element set with the selected basis element to produce a selection score; determining whether the selection score indicates an improvement in optimization for the basis element set; and discarding the basis element if the selection score does not indicate an improvement.