ANNOUNCE: AI::Categorizer 0.04 -> CPAN

Hi,

The uploaded file

     AI-Categorizer-0.04.tar.gz

has entered CPAN as

   file: $CPAN/authors/id/K/KW/KWILLIAMS/AI-Categorizer-0.04.tar.gz
   size: 243180 bytes
    md5: e4b60cb505544ee2a8d8d02a36b06a0e




Changes since 0.03:

  - Added learners for SVMs, Decision Trees, and a pass-through to
    Weka.

  - Added a virtual class for binary classifiers.

  - Wrote documentation for lots of the undocumented classes.

  - Added a PNG file giving an overview diagram of the classes.

  - Added a script 'categorizer' to provide a simple command-line
    interface to AI::Categorizer

  - save_state() and restore_state() now save to a directory, not a
    file.

  - Removed F1(), precision(), recall(), etc. from Util package since
    they're in Statistics::Contingency.  Added random_elements() to
    Util.

  - Collection::Files now warns when no category information is known
    about a document in the collection (knowing it's in zero categories
    is okay).

  - Added the Collection::InMemory class

  - Much more thorough testing with 'make test'.

  - Added add_hypothesis() method to Experiment.

  - Added dot() and value() methods to FeatureVector.

  - Added 'feature_selection' parameter to KnowledgeSet.

  - Added document($name) accessor method to KnowledgeSet.

  - In KnowledgeSet, load(), read(), and scan_*() can now accept a
    Collection object.

  - Added document_frequency(), finish(), and weigh_features() methods
    to KnowledgeSet.

  - Added save_features() and restore_features() to KnowledgeSet.

  - Added default categories() and categorize() methods to Learner base
    class.  get_scores() is now abstract.

  - Extended interface of ObjectSet class with retrieve(), includes(),
    and includes_name().

  - Moved 'term_weighting' parameter from Document to KnowledgeSet,
    since the normalized version needs to know the maximum
    term-frequency.  Also changed its values to 'n', 'l', 'b', and 't',
    with 'x' a synonym for 't'.

  - Implemented full range of TF/IDF term weighting methods (see Salton
    & Buckley, "Term Weighting Approaches in Automatic Text Retrieval",
    in journal "Information Processing & Management", 1988 #5)


  -Ken