1. A method for creating a classification rule by combining classifiers comprising: receiving N training samples d, wherein each of the N training samples d includes a label l; receiving T classifiers C; initializing a first random weight vector α for the N training samples d; initializing a second random weight vector β for the T classifiers C; creating, by a processor, the classification rule by identifying a combination of one or more of the T classifiers C that best approximates the label l for each of the N training samples d based on the first random weight vector and the second random weight vector β.