1. A method performed by a computer system for combining multiple classifiers, comprising: for each classifier, setting to zero multipliers associated with data elements that were not used to construct the classifier; and constructing a combined classifier by setting its multiplier values to a weighted average of the multipliers associated with the multiple classifiers wherein a combined support vector machine associated with a classifier 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)}).
1. A method performed by a computer system for combining multiple classifiers, comprising: for each classifier, setting to zero multipliers associated with data elements that were not used to construct the classifier; and constructing a combined classifier by setting its multiplier values to a weighted average of the multipliers associated with the multiple classifiers wherein a combined support vector machine associated with a classifier 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)}). 4. The method of claim 1 wherein the weight for each of the multiplier values associated with a support vector machine is computed based on one minus a fraction of points in a training data subset that is used to construct the classifier.