1. A computer-based method for classifying an observation of a set of observations, the method comprising: receiving the set of observations; classifying members of the set of observations as one of a first and a second type; modeling a probability density of the set of observations by assigning a first set of probabilities to members of the set of observations classified as said first type and a second set of probabilities to members of the set of observations classified as said second type, wherein at least one member of said first set of probabilities is greater than the members of said second set of probabilities; revising said probability density to reduce one or more of said second set of probabilities; receiving the observation; and classifying the observation according to said revised probability density.