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	warn "Can't parse line $line";
	next;
      }
      my ($index, $predicted, $score) = ($1, $2, $3);
      $assigned[$index]{$cat} = $score if $predicted;  # Not sure what weka's scores represent
      print STDERR "$index: assigned=($predicted) correct=(", $alldocs[$index]->is_in_category($cat) ? 1 : 0, ")\n"
	if $self->verbose;
    }
  }

  my $experiment = $self->create_delayed_object('experiment', categories => [map $_->name, $self->categories]);
  foreach my $i (0..$#alldocs) {
    $experiment->add_result([keys %{$assigned[$i]}], [map $_->name, $alldocs[$i]->categories], $alldocs[$i]->name);
  }

  return $experiment;
}


sub do_cmd {
  my ($self, @cmd) = @_;
  print STDERR " % @cmd\n" if $self->verbose;
  
  my @output;
  local *KID_TO_READ;
  my $pid = open(KID_TO_READ, "-|");
  
  if ($pid) {   # parent
    @output = <KID_TO_READ>;
    close(KID_TO_READ) or warn "@cmd exited $?";
    
  } else {      # child
    exec(@cmd) or die "Can't exec @cmd: $!";
  }
  
  return @output;
}

sub create_arff_file {
  my ($self, $name, $docs, $dir) = @_;
  $dir = $self->{model}{_in_dir} unless defined $dir;

  my ($fh, $filename) = File::Temp::tempfile(
					     $name . "_XXXX",  # Template
					     DIR    => $dir,
					     SUFFIX => '.arff',
					    );
  print $fh "\@RELATION foo\n\n";
  
  my $feature_names = $self->{model}{all_features};
  foreach my $name (@$feature_names) {
    print $fh "\@ATTRIBUTE feature-$name REAL\n";
  }
  print $fh "\@ATTRIBUTE category {1, 0}\n\n";
  
  my %feature_indices = map {$feature_names->[$_], $_} 0..$#{$feature_names};
  my $last_index = keys %feature_indices;
  
  # We use the 'sparse' format, see http://www.cs.waikato.ac.nz/~ml/weka/arff.html
  
  print $fh "\@DATA\n";
  foreach my $doc (@$docs) {
    my ($features, $cat) = @$doc;
    my $f = $features->as_hash;
    my @ordered_keys = (sort {$feature_indices{$a} <=> $feature_indices{$b}} 
			grep {exists $feature_indices{$_}}
			keys %$f);

    print $fh ("{",
	       join(', ', map("$feature_indices{$_} $f->{$_}", @ordered_keys), "$last_index '$cat'"),
	       "}\n"
	      );
  }
  
  return $filename;
}

sub save_state {
  my ($self, $path) = @_;

  {
    local $self->{knowledge_set};
    $self->SUPER::save_state($path);
  }
  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