my $positive = {
    word1 => 2,
    word2 => 4,
    word3 => 1,
};

##</code><code>##

sub invert_string {
       my ($string, $weight, $hash) = @_;
       $hash->{$_} += $weight for
            grep { !$StopWords{$_} }
            @{words(lc($string))};
    }
##</code><code>##

my $sentence1 = {
    wordA => 2,
    wordB => 1,
};

##</code><code>##

sub invert_item {
        my $item = shift;
        my %hash;
        invert_string($item->{title}, 2, \%hash);
        invert_string($item->{description}, 1, \%hash);
        return \%hash;
    }

##</code><code>##

 #!/usr/bin/perl

    use XML::RSS;
    use Algorithm::NaiveBayes;
    use Lingua::EN::Splitter qw(words);
    use Lingua::EN::StopWords qw(%StopWords);

    my $nb = Algorithm::NaiveBayes->new(  );

    for my $category (qw(interesting boring)) {
        my $rss = new XML::RSS;
        $rss->parsefile("$category.rdf");
        $nb->add_instance(attributes => invert_item($_),
                          label      => $category) for @{$rss->{'items'}};
    }

    $nb->train; # Work out all the probabilities

##</code><code>##

 my $rss = new XML::RSS;
        $rss->parsefile("$category.rdf");
       $nb->add_instance(attributes => invert_item($_),
                          label      => $category) for @{$rss->{'items'}};
    }