10. A system for combining multiple support vector machines, comprising: a computing device having a central processing unit and memory; a component that computes at least two Lagrange multipliers, each Lagrange multiplier computed to construct a support vector machine based on a subset of original training data that is randomly selected from the original training data; and a combined support vector machine, the combined support vector machine computed based at least in part on an aspect of the support vector machines based on the subsets of original training data, wherein the combined support vector machine receives an input, x, and computes a classification for the received input as ĝ(x)=ψ(Σ i=1 l {circumflex over (α)} i y i K(x i ,x)+{circumflex over (b)}).
10. A system for combining multiple support vector machines, comprising: a computing device having a central processing unit and memory; a component that computes at least two Lagrange multipliers, each Lagrange multiplier computed to construct a support vector machine based on a subset of original training data that is randomly selected from the original training data; and a combined support vector machine, the combined support vector machine computed based at least in part on an aspect of the support vector machines based on the subsets of original training data, wherein the combined support vector machine receives an input, x, and computes a classification for the received input as ĝ(x)=ψ(Σ i=1 l {circumflex over (α)} i y i K(x i ,x)+{circumflex over (b)}). 12. The system of claim 10 wherein the combined support vector machine is computed based at least in part on classifications of the original training data produced by the support vector machines.