AI::Categorizer::Hypothesis--3pm

AI::Categorizer::HypotUsersContributed Perl DoAI::Categorizer::Hypothesis(3pm)



NAME
       AI::Categorizer::Hypothesis - Embodies a set of category assignments

SYNOPSIS
        use AI::Categorizer::Hypothesis;

        # Hypotheses are usually created by the Learner's categorize() method.
        # (assume here that $learner and $document have been created elsewhere)
        my $h = $learner->categorize($document);

        print "Assigned categories: ", join ', ', $h->categories, "\n";
        print "Best category: ", $h->best_category, "\n";
        print "Assigned scores: ", join ', ', $h->scores( $h->categories ), "\n";
        print "Chosen from: ", join ', ', $h->all_categories, "\n";
        print +($h->in_category('geometry') ? '' : 'not '), "assigned to geometry\n";

DESCRIPTION
       A Hypothesis embodies a set of category assignments that a categorizer
       makes about a single document.  Because one may be interested in know-
       ing different kinds of things about the assignments (for instance, what
       categories were assigned, which category had the highest score, whether
       a particular category was assigned), we provide a simple class to help
       facilitate these scenarios.

METHODS
       new(%parameters)
           Returns a new Hypothesis object.  Generally a user of "AI::Catego-
           rize" doesn't create a Hypothesis object directly - they are
           returned by the Learner's "categorize()" method.  However, if you
           wish to create a Hypothesis directly (maybe passing it some fake
           data for testing purposes) you may do so using the "new()" method.

           The following parameters are accepted when creating a new Hypothe-
           sis:

           all_categories
               A required parameter which gives the set of all categories that
               could possibly be assigned to.  The categories should be speci-
               fied as a reference to an array of category names (as strings).

           scores
               A hash reference indicating the assignment score for each cate-
               gory.  Any score higher than the "threshold" will be considered
               to be assigned.

           threshold
               A number controlling which categories should be assigned - any
               category whose score is greater than or equal to "threshold"
               will be assigned, any category whose score is lower than
               "threshold" will not be assigned.

           document_name
               An optional string parameter indicating the name of the docu-
               ment about which this hypothesis was made.

       categories()
           Returns an ordered list of the categories the document was placed
           in, with best matches first.  Categories are returned by their
           string names.

       best_category()
           Returns the name of the category with the highest score in this
           hypothesis.

       in_category($name)
           Returns true or false depending on whether the document was placed
           in the given category.

       scores(@names)
           Returns a list of result scores for the given categories.  Since
           the interface is still changing, and since different Learners
           implement scoring in different ways, not very much can officially
           be said about the scores, except that a good score is higher than a
           bad score.  Individual Learners will have their own procedures for
           determining scores, so you cannot compare one Learner's score with
           another Learner's - for instance, one Learner might always give
           scores between 0 and 1, and another Learner might always return
           scores less than 0.  You often cannot compare scores from a single
           Learner on two different categorization tasks either.

       all_categories()
           Returns the list of category names specified with the "all_cate-
           gories" constructor parameter.

       document_name()
           Returns the value of the "document_name" parameter specified as a
           constructor parameter, or "undef" if none was specified.

AUTHOR
       Ken Williams <ken AT mathforum.org>

COPYRIGHT
       This distribution is free software; you can redistribute it and/or mod-
       ify it under the same terms as Perl itself.  These terms apply to every
       file in the distribution - if you have questions, please contact the
       author.



perl v5.8.7                       2002-11-24  AI::Categorizer::Hypothesis(3pm)