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RPM resource perl-Statistics-MaxEntropy

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.

Found 1 sites for perl-Statistics-MaxEntropy

• http://search.cpan.org/dist/Statistics-MaxEntropy/

Found 13 RPM for perl-Statistics-MaxEntropy

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Fabrice Bellet