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osbf-lua.luaforge.net

OSBF-Lua

Text classification module for the Lua. And a production class anti-spam in Lua using the module. 1 in CEAS 2008 Spam Filter Live Challenge. Winner of TREC's Spam Track 2006. Igrams with confidence F. Actor) is a Lua. C module for text classification. It is a port of the OSBF classifier implemented in the CRM114. The OSBF algorithm is a typical Bayesian classifier but enhanced with two techniques that I originally developed for the CRM114 project: Orthogonal Sparse Bigrams. And in CEAS 2008 Live Challenge.

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OSBF-Lua | osbf-lua.luaforge.net Reviews
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Text classification module for the Lua. And a production class anti-spam in Lua using the module. 1 in CEAS 2008 Spam Filter Live Challenge. Winner of TREC's Spam Track 2006. Igrams with confidence F. Actor) is a Lua. C module for text classification. It is a port of the OSBF classifier implemented in the CRM114. The OSBF algorithm is a typical Bayesian classifier but enhanced with two techniques that I originally developed for the CRM114 project: Orthogonal Sparse Bigrams. And in CEAS 2008 Live Challenge.
<META>
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1 osbf lua
2 programming language
3 overview
4 middot;
5 what's new
6 download and contributions
7 installation
8 manual
9 credits
10 osbf lua o
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osbf lua,programming language,overview,middot;,what's new,download and contributions,installation,manual,credits,osbf lua o,rthogonal s,parse b,eddc,aka confidence factor,spamfilter lua,the confidence factor,are also available,in the 8,this distribution
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OSBF-Lua | osbf-lua.luaforge.net Reviews

https://osbf-lua.luaforge.net

Text classification module for the Lua. And a production class anti-spam in Lua using the module. 1 in CEAS 2008 Spam Filter Live Challenge. Winner of TREC's Spam Track 2006. Igrams with confidence F. Actor) is a Lua. C module for text classification. It is a port of the OSBF classifier implemented in the CRM114. The OSBF algorithm is a typical Bayesian classifier but enhanced with two techniques that I originally developed for the CRM114 project: Orthogonal Sparse Bigrams. And in CEAS 2008 Live Challenge.

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http://osbf-lua.luaforge.net/TREC2005

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OSBF-Lua

http://osbf-lua.luaforge.net/manual.html

Text classification module for the Lua. Igrams with confidence F. Actor) is a Lua. C module for text classification. It is a port of the OSBF classifier implemented in the. Project. This implementation attempts to put focus on the classification task itself by using Lua as the scripting language, a powerful yet light-weight and fast language, which makes it easier to build and test more elaborated filters and training methods. This distribution includes a copy of the license in the file gpl.txt. Ncfs = 1,.

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siefkes.net siefkes.net

A Training Script for OSBF-Lua - Christian Siefkes

http://www.siefkes.net/software/trainfilter

A Training Script for OSBF-Lua. Filter written by Fidelis Assis is an amazing spam filter, which is, however, somewhat hard to train. The filter requires feedback when it has misclassified an email or when it is uncertain about classification ("reinforcement training"). The "normal" way to train is to reply to yourself with a re-classification command in the subject line, which is a somewhat complicated and error-prone process. This version was created by Christian Siefkes. If you didn't install Lua in.

jhweiss.de jhweiss.de

OSBF-Lua Stuff

http://www.jhweiss.de/software/osbf-lua.html

Module for text classification written by Fidelis Assis which includes an extremely fast and effective spam filter. Trains the OSBF-Lua spam filter using the e-mails from a given ham and/or a given spam folder (both of them are expected to be in mbox format. Note that OSBF-Lua learns so quickly. That a pre-training of the spam filter won't be necessary in most cases. However,. Might be useful for ISP. As an alternative solution for this purpose. See the output of. Train osbf.lua - help.

siefkes.net siefkes.net

Moonfilter - Christian Siefkes

http://www.siefkes.net/software/moonfilter

Moonfilter is a general-purpose text classifier based on OSBF-Lua. It is usable both as a Lua module. Or as stand-alone script. That can easily be controlled from the command-line. Moonfilter has been written by Christian Siefkes. And is licensed under the GPL. The Moonfilter API includes:. A function for setting the classes to classify among (which will be used for all subsequent operations);. Functions for creating and destroying the database files;. The API also exports some public variables so the us...

siefkes.net siefkes.net

Spam Filtering and Text Classification - Christian Siefkes

http://www.siefkes.net/spam

Spam Filtering and Text Classification. Spam is ubiquitous, highly adapting to any counter-measures, and most annoying. This makes spam filtering one of the most important and interesting research topics in the field of text classification and text mining. During the course of my research, I have cooperated with the spam filtering geniuses Bill Yerazunis ( CRM114. And Fidelis Assis ( OSBF-Lua. GPL): The two excellent spam filter and general-purpose text classifiers I've been involved with. This wasn't th...

siefkes.net siefkes.net

Free Software - Christian Siefkes

http://www.siefkes.net/software

I have contributed to various free software projects, and have also written a few (mostly small) programs of my own. GPL): The two excellent spam filter and general-purpose text classifiers I've been involved with. Perl, public domain): A small script that makes it easier to train the OSBF-Lua spam filter, converting the training process into a drag-and-drop operation. The software I've written during my PhD project is called Trainable Information Extractor. And then there's NL Stego. For example) and th...

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Text classification module for the Lua. And a production class anti-spam in Lua using the module. 1 in CEAS 2008 Spam Filter Live Challenge. Winner of TREC's Spam Track 2006. Igrams with confidence F. Actor) is a Lua. C module for text classification. It is a port of the OSBF classifier implemented in the CRM114. The OSBF algorithm is a typical Bayesian classifier but enhanced with two techniques that I originally developed for the CRM114 project: Orthogonal Sparse Bigrams. And in CEAS 2008 Live Challenge.

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