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perl-Statistics-MaxEntropy-0.9-15.src.rpm

Description:

This module is an implementation of the Generalised and Improved
Iterative Scaling (GIS, IIS) algorithms and the Feature Induction (FI)
algorithm as defined in (Darroch and Ratcliff 1972) and (Della Pietra
et al. 1997). The purpose of the scaling algorithms is to find the
maximum entropy distribution given a set of events and (optionally) an
initial distribution. Also a set of candidate features may be
specified; then the FI algorithm may be applied to find and add the
candidate feature(s) that give the largest `gain' in terms of Kullback
Leibler divergence when it is added to the current set of features.

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