Say you have three files: positive, negative, and the sentences to test. They are already prepared and are in this format:

wordA wordB wordC
wordD wordA wordE wordF
[download]

To train you would feed the first two files in:

my $pos_file = '/path/to/positive.txt';
my $neg_file = '/path/to/negative.txt';

my $categorizer = Algorithm::NaiveBayes->new;
my $fh;

open($fh,"<",$pos_file) or die "Could not open $pos_file: $!";
while (my $sentence = <$fh>) {
    chomp $sentence;
    my @words = split(' ',$sentence);
    my %positive;
    $positive{$_}++ for @words;
    $categorizer->add_instance(
        attributes => \%positive,
        label => 'positive');
}
close($fh);

open($fh,"<",$neg_file) or die "Could not open $neg_file: $!";
while (my $sentence = <$fh>) {
    chomp $sentence;
    my @words = split(' ',$sentence);
    my %negative;
    $negative{$_}++ for @words;
    $categorizer->add_instance(
        attributes => \%negative,
        label => 'negative');
}
close($fh);

$categorizer->train;
[download]

You can then feed the third file in:

my $sentence_file = '/path/to/sentence.txt';

open($fh,"<",$sentence_file) or die "Could not open $sentence_file: $!
+";
while (my $sentence = <$fh>) {
    chomp $sentence;
    my @words = split(' ',$sentence);
    my %test;
    $test{$_}++ for @words;
    my $probability = $categorizer->predict(attributes => \%test);
    # ...
    # do what you need with $probability
}
close($fh);
[download]

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