Figure 2.
Feature Binning. To bin a set of terms, we first partition the continuous probability interval [0,1] into equal-spaced sub-intervals, each of width w. Two terms and
are grouped into one bin if and only if the probability
falls into the same probability sub-interval as
, and
falls into the same probability sub-interval as
.