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t/02-learn_by_lbfgs.t  view on Meta::CPAN

use strict;
use warnings;

use Test::More tests => 5;
use Test::Number::Delta within => 1e-5;

my $__;
sub NAME { $__ = shift };

###
NAME 'Load the module';
BEGIN { use_ok 'AI::MaxEntropy' }

my $me = AI::MaxEntropy->new(smoother => {}); 
$me->see(['round', 'smooth', 'red'] => 'apple' => 2);
$me->see(['long', 'smooth', 'yellow'] => 'banana' => 3);
$me->cut(0);
$me->_cache;

###
NAME 'Negative log likelihood calculation (lambda = all 0)';
my ($f, $g) = AI::MaxEntropy::_neg_log_likelihood(
    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], undef, $me
);
delta_ok
[
    $f,
    $g
],
[
    - (2 * log(0.5) + 3 * log(0.5)),
    [
	- ((1 - 0.5) * 2 + 0 * 3),
	- ((1 - 0.5) * 2 + (0 - 0.5) * 3),
	- ((1 - 0.5) * 2 + 0 * 3),
        - (0 * 2 + (0 - 0.5) * 3),
	- (0 * 2 + (0 - 0.5) * 3),
	- ((0 - 0.5) * 2 + 0 * 3),
	- ((0 - 0.5) * 2 + (1 -0.5) * 3),
	- ((0 - 0.5) * 2 + 0 * 3),
	- (0 * 2 + (1 - 0.5) * 3),
	- (0 * 2 + (1 - 0.5) * 3)
    ]
],
$__;

###
NAME 'Negative log likelihood calculation (lambda = random .1 and 0)';
($f, $g) = AI::MaxEntropy::_neg_log_likelihood(
    [.1, .1, 0, 0, 0, .1, .1, 0, 0, .1], undef, $me
);
delta_ok
[
    $f,
    $g
],
[
    - (log(exp(.1) / (2 * exp(.1))) * 2 +
       log(exp(.2) / (exp(.1) + exp(.2))) * 3),
    [
	- ((1 - exp(.1) / (2 * exp(.1))) * 2 + 0 * 3),
	- ((1 - exp(.1) / (2 * exp(.1))) * 2 + 
	   (0 - exp(.1) / (exp(.1) + exp(.2))) * 3),
	- ((1 - exp(.1) / (2 * exp(.1))) * 2 + 0 * 3),