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.
