| Name : perl-Statistics-MaxEntropy
| |
| Version : 0.9
| Vendor : Dag Apt Repository, http://dag_wieers_com/apt/
|
| Release : 1.0.el2.rf
| Date : 2005-05-02 16:21:28
|
| Group : Applications/CPAN
| Source RPM : perl-Statistics-MaxEntropy-0.9-1.0.el2.rf.src.rpm
|
| Size : 0.11 MB
| |
| Packager : Dries Verachtert < dries_ulyssis_org>
| |
| Summary : Maximum Entropy Modeling and Feature Induction
|
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.
|
RPM found in directory: /vol/rzm3/linux-dag/dag/redhat/el2.1/en/i386/dag/RPMS |
