Forming Equivalence Classes I
Classification Problem: try to predict the target feature based on various classificatory features. ==> Reliability versus discrimination
Markov Assumption: Only the prior local context affects the next entry: (n-1)th Markov Model or n- gram
Size of the n-gram models versus number of parameters: we would like n to be large, but the number of parameters increases exponentially with n.
There exist other ways to form equivalence classes of the history, but they require more complicated . methods ==> will use n-grams here.