https://github.com/pmundkur/libcrm114

C library version of CRM114, and a Python binding
https://github.com/pmundkur/libcrm114

Last synced: 30 days ago
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C library version of CRM114, and a Python binding

• Host: GitHub
• URL: https://github.com/pmundkur/libcrm114
• Owner: pmundkur
• Created: 2011-11-22T02:16:36.000Z (almost 13 years ago)
• Default Branch: master
• Last Pushed: 2013-04-07T20:35:11.000Z (over 11 years ago)
• Last Synced: 2024-07-31T22:56:51.713Z (3 months ago)
• Language: C
• Homepage: http://crm114.sourceforge.net/wiki/doku.php?id=download
• Size: 383 KB
• Stars: 14
• Watchers: 4
• Forks: 7
• Open Issues: 2
• Metadata Files:
  • Readme: README

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README

        
From http://crm114.sourceforge.net/wiki/doku.php?id=download:

CRM114 C-callable Library

This is the callable library version of CRM114. It has most of the

classifiers as the standalone language (with some significant

improvements- one alpha tester says they saw a 10x speedup in their

application). This version is LGPLed (Library GPL) so you can link it

with your own code, whether open-source or proprietary. You still need

TRE (on Fedora, “yum install tre-devel”). Note that with improvements

come costs: libcrm114 classifiers are NOT compatible with standalone

CRM114 class files (necessary, because libcrm114 classifiers can work

even on systems that don't have filesystems, like embedded

processors). The code is now pretty stable and the API solidly

entrenched by use in several real products, so the api is unlikely to

change in unpleasant ways.

Advantages of libcrm114: It's much faster; everything is

in-memory. You can call everything directly from ANSI C. Because

everything is in memory, it's good for embedded systems where you

don't _have_ a unix-style file system to talk to. No arcane language

to learn, it's all just ANSI C. You can export classifiers as ASCII

“CSV-like” format so trained classifiers are 32/64-bit portable and

cross-platform Linux/Mac/Windows portable (the internal binary

classifier format is still tied to a particular architecture, but

that's never exported any more).

Disadvantages of libcrm114: Not all classifiers are currently

supported (in particular, Neural Net, Correllator, OSBF, and Winnow

are NOT yet supported). There's no crazy language, so you need to get

your data into memory on your own. You still need TRE. You do pay a

(not horrible) startup cost loading a classifier from a an ASCII

CSV-like file, but since you can then reuse the classifier for as many

documents as you want, in the long term this cost is amortized down to

zero and you get significant speedup.

Dependencies

Debian/Ubuntu: libtre5, libtre-dev

Building

$ make && cd python && python setup build