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Rather than reweighting in a vector space…
If user has told us some relevant and some nonrelevant documents, then we can proceed to build a probabilistic classifier
such as the Naive Bayes model we will look at today:
P(tk|R) = |Drk| / |Dr|
P(tk|NR) = |Dnrk| / |Dnr|
tk is a term; Dr is the set of known relevant documents; Drk is the subset that contain tk; Dnr is the set of known nonrelevant documents; Dnrk is the subset that contain tk.
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