Esempi in PHP per Neural BackpropagationTeacher

Esempio n. 1

File: digit_count.php Progetto: a1essandro/neural-network

<?php

use Neural\BackpropagationTeacher;
use Neural\MultilayerPerceptron;
require_once '../vendor/autoload.php';
$p = new MultilayerPerceptron([4, 4, 5]);
$p->generateSynapses();
$t = new BackpropagationTeacher($p);
echo $t->teachKit([[0, 0, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0], [0, 1, 0, 0], [1, 0, 0, 0], [1, 0, 0, 1], [0, 1, 1, 0], [1, 1, 0, 0], [0, 0, 1, 1], [1, 0, 1, 0], [0, 1, 0, 1], [0, 1, 1, 1], [1, 0, 1, 1], [1, 1, 0, 1], [1, 1, 1, 0], [1, 1, 1, 1]], [[1, 0, 0, 0, 0], [0, 1, 0, 0, 0], [0, 1, 0, 0, 0], [0, 1, 0, 0, 0], [0, 1, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 1]], 0.25) . PHP_EOL;
$roundElements = function (&$r) {
    $r = round($r);
};
$test = [rand(0, 1), rand(0, 1), rand(0, 1), rand(0, 1)];
$result = $p->input($test)->output();
array_walk($result, $roundElements);
echo 'Result for [' . implode(', ', $test) . ']:' . PHP_EOL;
echo '[' . implode(', ', $result) . ']';

Esempio n. 2

File: performance_test.php Progetto: a1essandro/neural-network

<?php

use Neural\BackpropagationTeacher;
use Neural\MultilayerPerceptron;
require_once '../vendor/autoload.php';
$p = new MultilayerPerceptron([4, 8, 5]);
$p->generateSynapses();
$t = new BackpropagationTeacher($p);
$startTime = microtime(true);
$epochs = $t->teachKit([[0, 0, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0], [0, 1, 0, 0], [1, 0, 0, 0], [1, 0, 0, 1], [0, 1, 1, 0], [1, 1, 0, 0], [0, 0, 1, 1], [1, 0, 1, 0], [0, 1, 0, 1], [0, 1, 1, 1], [1, 0, 1, 1], [1, 1, 0, 1], [1, 1, 1, 0], [1, 1, 1, 1]], [[1, 0, 0, 0, 0], [0, 1, 0, 0, 0], [0, 1, 0, 0, 0], [0, 1, 0, 0, 0], [0, 1, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 1]], 0.25) . PHP_EOL;
$endTime = microtime(true);
echo 'Memory peak usage: ' . round(memory_get_peak_usage() / 1024, 1) . PHP_EOL;
echo 'Seconds per epoch: ' . round(($endTime - $startTime) / $epochs, 3);

Esempio n. 3

File: demo.php Progetto: a1essandro/neural-network

<?php

use Neural\BackpropagationTeacher;
use Neural\MultilayerPerceptron;
require_once '../vendor/autoload.php';
//Creation neural network, with 2 input-neurons, one hidden layer with 2 neurons and one output neuron:
$p = new MultilayerPerceptron([2, 2, 1]);
//You may add more hidden layers or neurons to layers: [2, 3, 2, 1]
$p->generateSynapses();
//automatically add synapses
$p->trace();
$t = new BackpropagationTeacher($p);
//Teacher with backpropagation algorithm
//Teach until it learns
$learningResult = $t->teachKit([[1, 0], [0, 1], [1, 1], [0, 0]], [[1], [1], [0], [0]], 0.3, 10000);
if ($learningResult != -1) {
    echo '1,0: ' . round($p->input([1, 0])->output()[0]) . PHP_EOL;
    echo '0,1: ' . round($p->input([0, 1])->output()[0]) . PHP_EOL;
    echo '0,0: ' . round($p->input([0, 0])->output()[0]) . PHP_EOL;
    echo '1,1: ' . round($p->input([1, 1])->output()[0]) . PHP_EOL;
}
$p->trace();