Cyber Challenge: 10,000 Security Warriors Wanted

 
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Old 05-25-2010
Cyber Challenge: 10,000 Security Warriors Wanted

by Dian Schaffhauser,* Campus Technology The Cyber Challenge has set as its national goal to identify and train an army of cybersecurity experts to help fill shortages in industry and government. Campuses like Cal Poly are helping to lead the charge. Karen Evans understands the need for online security–and for people who really know how to implement [...]

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fst-train(1)							     fst-train							      fst-train(1)

NAME
fst-train - learning transducer weights SYNOPSIS
fst-train [ options ] file [ input-file ] OPTIONS
-t file use multiple transducers in the same way as fst-infl2. -b This option is used for supervised training with disambiguated data. -d Disambiguate the analyses symbolically as described in the man pages of fst-infl2. -q quiet mode DESCRIPTION
fst-train is used to learn statistical weights for the transducers transitions based on training data. Training is either unsupervised (default) or supervised (option -b). In supervised mode, the input contains fully disambiguated data with the surface and the analysis form. The format restrictions are identi- cal to those applying for lexicon entries, i.e. all operators other than the colon operator (:) are interpreted literally. In unsupervised mode, the input data consists of surface strings. The format is identical to the input format of fst-infl and fst-infl2. The transducer weights are stored in files whose names are obtained by appending .prob to the names of the transducer files. BUGS
No bugs are known so far. SEE ALSO
fst-infl2, fst-compiler AUTHOR
Helmut Schmid, Institute for Computational Linguistics, University of Stuttgart, Email: schmid@ims.uni-stuttgart.de, This software is available under the GNU Public License. October 2005 fst-train(1)