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In practical settings there is seldom sufficient data to accurately estimate the [[exponent|exponential]] growing number of [[conditional probability]] components as the order of the [[Markov chain]] increases.
The Variable Order Markov model assumes that in realistic settings, there are certain realizations of states (represented by contexts) in which some past states are independent from the future states, accordingly, ''a great reduction in the number of model parameters can be achieved''.
==Application Areas==
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