12. The apparatus of claim 11 , wherein the boosting module is a smooth boosting module.
11. An apparatus for generating a classifier from examples in a dataset containing malicious noise, comprising: a memory containing at least one of the examples of the dataset, wherein the at least one examples stored in the memory contains malicious noise; and a processor having access to the memory, the processor configured to: execute a boosting module to repeatedly call a weak learner module that generates as output a plurality of weak classifiers selected from a plurality of candidate classifiers, wherein at least some of the plurality of candidate classifiers comprise a majority vote over a plurality of randomly-generated classifiers as applied to the at least one example stored in the memory, wherein the plurality of randomly-generated classifiers has a cardinality that is a function of a size of a margin of the randomly-generated classifiers; and generate a classifier that incorporates at least some of the plurality of weak classifiers.