10. A method comprising: projecting a set of training vectors in a vector space to a comparison space defined by a set of reference vectors using a comparison function to generate a corresponding set of projected training vectors in the comparison space; training a linear classifier on the set of projected training vectors to generate a trained linear classifier operative in the comparison space; and transforming the trained linear classifier operative in the comparison space into a trained nonlinear classifier operative in the vector space; wherein the projecting, the training, and the transforming are performed by a digital processing device; and wherein the set of reference vectors is selected from a group consisting of: the set of training vectors, the set of training vectors plus additional vectors in the vector space, a subset of the set of training vectors plus additional vectors in the vector space, and a set of vectors in the vector space that is disjoint from the set of training vectors.
11. A computer programmed to classify an input vector using a trained nonlinear classifier operative in a vector space and generated by a method as set forth in claim 10 .