AI::Categorizer::Learner::Guesser - Simple guessing based on class probabilities
use AI::Categorizer::Learner::Guesser;
# Here $k is an AI::Categorizer::KnowledgeSet object
my $l = new AI::Categorizer::Learner::Guesser;
$l->train(knowledge_set => $k);
$l->save_state('filename');
... time passes ...
$l = AI::Categorizer::Learner->restore_state('filename');
my $c = new AI::Categorizer::Collection::Files( path => ... );
while (my $document = $c->next) {
my $hypothesis = $l->categorize($document);
print "Best assigned category: ", $hypothesis->best_category, "\n";
print "All assigned categories: ", join(', ', $hypothesis->categories), "\n";
}
This implements a simple category guesser that makes assignments based solely on
the prior probabilities of categories. For instance, if 5% of the training
documents belong to a certain category, then the probability of any test
document being assigned to that category is 0.05. This can be useful for
providing baseline scores to compare with other more sophisticated algorithms.
See AI::Categorizer for a complete description of the
interface.
This class inherits from the
"AI::Categorizer::Learner" class, so all of
its methods are available.
Ken Williams ("<ken@mathforum.org>")
Copyright 2000-2003 Ken Williams. All rights reserved.
This library is free software; you can redistribute it and/or
modify it under the same terms as Perl itself.