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  return unless $self->{model};

  my $model_dir = File::Spec->catdir($path, 'models');
  mkdir($model_dir, 0777) or die "Couldn't create $model_dir: $!";
  while (my ($name, $learner) = each %{$self->{model}{learners}}) {
    my $oldpath = File::Spec->catdir($self->{model}{_in_dir}, $learner->{machine_file});
    my $newpath = File::Spec->catfile($model_dir, "${name}_model");
    File::Copy::copy($oldpath, $newpath);
  }
  $self->{model}{_in_dir} = $model_dir;
}

sub restore_state {
  my ($pkg, $path) = @_;
  
  my $self = $pkg->SUPER::restore_state($path);

  my $model_dir = File::Spec->catdir($path, 'models');
  return $self unless -e $model_dir;
  $self->{model}{_in_dir} = $model_dir;
  
  return $self;
}

1;

__END__

=head1 NAME

AI::Categorizer::Learner::Weka - Pass-through wrapper to Weka system

=head1 SYNOPSIS

  use AI::Categorizer::Learner::Weka;
  
  # Here $k is an AI::Categorizer::KnowledgeSet object
  
  my $nb = new AI::Categorizer::Learner::Weka(...parameters...);
  $nb->train(knowledge_set => $k);
  $nb->save_state('filename');
  
  ... time passes ...
  
  $nb = AI::Categorizer::Learner->restore_state('filename');
  my $c = new AI::Categorizer::Collection::Files( path => ... );
  while (my $document = $c->next) {
    my $hypothesis = $nb->categorize($document);
    print "Best assigned category: ", $hypothesis->best_category, "\n";
  }

=head1 DESCRIPTION

This class doesn't implement any machine learners of its own, it
merely passes the data through to the Weka machine learning system
(http://www.cs.waikato.ac.nz/~ml/weka/).  This can give you access to
a collection of machine learning algorithms not otherwise implemented
in C<AI::Categorizer>.

Currently this is a simple command-line wrapper that calls C<java>
subprocesses.  In the future this may be converted to an
C<Inline::Java> wrapper for better performance (faster running
times).  However, if you're looking for really great performance,
you're probably looking in the wrong place - this Weka wrapper is
intended more as a way to try lots of different machine learning
methods.

=head1 METHODS

This class inherits from the C<AI::Categorizer::Learner> class, so all
of its methods are available unless explicitly mentioned here.

=head2 new()

Creates a new Weka Learner and returns it.  In addition to the
parameters accepted by the C<AI::Categorizer::Learner> class, the
Weka subclass accepts the following parameters:

=over 4

=item java_path

Specifies where the C<java> executable can be found on this system.
The default is simply C<java>, meaning that it will search your
C<PATH> to find java.

=item java_args

Specifies a list of any additional arguments to give to the java
process.  Commonly it's necessary to allocate more memory than the
default, using an argument like C<-Xmx130MB>.

=item weka_path

Specifies the path to the C<weka.jar> file containing the Weka
bytecode.  If Weka has been installed somewhere in your java
C<CLASSPATH>, you needn't specify a C<weka_path>.

=item weka_classifier

Specifies the Weka class to use for a categorizer.  The default is
C<weka.classifiers.NaiveBayes>.  Consult your Weka documentation for a
list of other classifiers available.

=item weka_args

Specifies a list of any additional arguments to pass to the Weka
classifier class when building the categorizer.

=item tmpdir

A directory in which temporary files will be written when training the
categorizer and categorizing new documents.  The default is given by
C<< File::Spec->tmpdir >>.

=back

=head2 train(knowledge_set => $k)

Trains the categorizer.  This prepares it for later use in
categorizing documents.  The C<knowledge_set> parameter must provide
an object of the class C<AI::Categorizer::KnowledgeSet> (or a subclass
thereof), populated with lots of documents and categories.  See
L<AI::Categorizer::KnowledgeSet> for the details of how to create such
an object.

=head2 categorize($document)

Returns an C<AI::Categorizer::Hypothesis> object representing the
categorizer's "best guess" about which categories the given document
should be assigned to.  See L<AI::Categorizer::Hypothesis> for more
details on how to use this object.

=head2 save_state($path)

Saves the categorizer for later use.  This method is inherited from
C<AI::Categorizer::Storable>.

=head1 AUTHOR

Ken Williams, ken@mathforum.org

=head1 COPYRIGHT

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.

=head1 SEE ALSO