[
https://issues.apache.org/jira/browse/UIMA-1833?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Fabien POULARD updated UIMA-1833:
---------------------------------
Original Estimate: (was: 0.17h)
Remaining Estimate: (was: 0.17h)
> Create an AE for training the HMM Tagger models
> -----------------------------------------------
>
> Key: UIMA-1833
> URL: https://issues.apache.org/jira/browse/UIMA-1833
> Project: UIMA
> Issue Type: Improvement
> Components: Sandbox-Tagger
> Environment: OS:
> Debian Linux Squeeze 64bits
> JVM:
> java version "1.6.0_20"
> Java(TM) SE Runtime Environment (build 1.6.0_20-b02)
> Java HotSpot(TM) 64-Bit Server VM (build 16.3-b01, mixed mode)
> Reporter: Fabien POULARD
> Priority: Minor
> Fix For: 2.3CE
>
>
> There is a class to train a model for the HMM Tagger out of a corpus.
> However, this is a standalone application that does not take advantage of the
> UIMA capabilities. It would be better to train such a model thanks to an
> analysis engine.
> A training CPE would be like :
> 1- a collection reader loading the gold standard corpus
> 2- the HMM Tagger model trainer analysis engine that would browse some
> specific annotation, extract the material to feed the learning algorithm and
> finally export a model file.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.