5. A method for training Markov Models comprising the steps of: identifying a first training set representing first sequences corresponding to a first classification; identifying a second training set representing second sequences, different than the first sequences, corresponding to a second classification; and establishing Markov Model parameters for the first classification based on the first and the second training sets.
5. A method for training Markov Models comprising the steps of: identifying a first training set representing first sequences corresponding to a first classification; identifying a second training set representing second sequences, different than the first sequences, corresponding to a second classification; and establishing Markov Model parameters for the first classification based on the first and the second training sets. 7. A method according to claim 5, wherein the establishing of the Markov Model parameters includes: generating Markov Model parameters corresponding to both the first sequences and the second sequences; and increasing those of the generated Markov Model parameters which correspond primarily to the first sequences and decreasing those of the generated Markov Model parameters which correspond primarily to the second sequences.