  We identify the classical Perceptron algorithm with margin as a member of a
broader family of large margin classifiers which we collectively call the
Margitron. The Margitron, (despite its) sharing the same update rule with the
Perceptron, is shown in an incremental setting to converge in a finite number
of updates to solutions possessing any desirable fraction of the maximum
margin. Experiments comparing the Margitron with decomposition SVMs on tasks
involving linear kernels and 2-norm soft margin are also reported.
