Bag Of Words Library README
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libbow, version BOW_VERSION.

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Rainbow
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Rainbow is a standalone program that does document classification.  Here are some examples:

  * rainbow -i ./training/positive ./training/negative

     Using the text files found under the directories ./positive and ./negative, tokenize, build word vectors, and write the resulting data structures to disk.

  * rainbow -q ./testing/254

     Tokenize the text document ./testing/254, and classify it, producing output like:

          /home/mccallum/training/positive 0.72
          /home/mccallum/training/negative 0.28

  * rainbow -t 5

     Perform 5 trials, each consisting of a test/train split, a resetting of weights according to the new split, and outputs of the classification of the test documents.

Typing rainbow --help will give list of all rainbow options.

After you have compiled libbow and rainbow, you can run the shell script ./demo/script to see an annotated demonstration of the classifier in action.

The web page http://www.cs.cmu.edu/afs/cs.cmu.edu/project/theo-11/www/naive-bayes.html has a pointer to a ``Gentle Introduction to Rainbow'', as well as some sample UseNet text data.

     Rainbow improvements coming soon:
        Better documentation.
        Better modularily of command-line options for changing parameters
          of weight-setting methods.
        Incremental model training.
        Better smoothing.  Good-Turing estimates, etc.

Arrow
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Arrow is a standalone program that does document retrieval. Sorry, there is no documentation yet.