1. A method comprising: receiving a training dataset comprising a plurality of tuples and a plurality of attributes for each of the tuples; deriving a plurality of granules from the training dataset, each granule comprising a plurality of sample tuples and a plurality of sample attributes; processing the granules using a support vector machine process to identify a hyperplane classifier associated with each of the granules; predicting a classification of a new tuple using each of the hyperplane classifiers to produce a plurality of predictions; and aggregating the predictions to derive a decision on a final classification of the new tuple.