1. A method of feature selection comprising: (a) selecting a weighted subset of (k−x) features associated with a target, either individually or in combination, k being a number greater than 1 and x being a number greater than 0 and less than k; (b) adding x complementary features to said subset to form a predictor set of k features; (c) selecting a counting threshold, T, that is greater than or equal to k; (d) checking to see if all of said k features of said predictor set have been repeated T times in a row; (e) if determined in step (d) that all of said features of said predictor set have not been repeated T times in a row, removing at least x features from said predictor set and returning to step (b); and (f) as a result of determining in step (d) that all of said features of said predictor set have been repeated T times in a row, then selecting such predictor set as a best predictor set of k features for predicting said target.