5. The method of claim 1 , further comprising using decision stumps as base classifiers.
1. A machine learning method having a multiple number of learning stages, each learning stage comprising: partitioning, using a computer processor, examples into bins; choosing, using a computer processor, a base classifier for each bin; and assigning, using a computer processor, an example to a bin by counting the number of positive predictions previously made by the base classifier associated with the bin.