1. A machine learning method, comprising: providing one or more training data samples having one or more known classes; training two or more learning machines comprising a sequential minimal optimization (SMO) algorithm to identify said one or more known classes using said one or more training data samples; modifying a core of the learning machine to adjust a weight assigned to individual training samples; selecting the trained learning machine that optimizes a performance function dependent on one or more variables between said one or more known classes; and outputting the selected trained learning machine into a computer memory.