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MDL-58859 mlbackend_php: Added to core

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Part of MDL-57791 epic.
This commit is contained in:
David Monllao
2017-07-24 07:51:54 +02:00
parent 229ae617c5
commit 9e84757bf0
129 changed files with 11485 additions and 0 deletions
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lib/mlbackend/php/phpml/src/Phpml/SupportVectorMachine/DataTransformer.php
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<?php
declare(strict_types=1);
namespace Phpml\SupportVectorMachine;
class DataTransformer
{
/**
* @param array $samples
* @param array $labels
* @param bool $targets
*
* @return string
*/
public static function trainingSet(array $samples, array $labels, bool $targets = false): string
{
$set = '';
if (!$targets) {
$numericLabels = self::numericLabels($labels);
}
foreach ($labels as $index => $label) {
$set .= sprintf('%s %s %s', ($targets ? $label : $numericLabels[$label]), self::sampleRow($samples[$index]), PHP_EOL);
}
return $set;
}
/**
* @param array $samples
*
* @return string
*/
public static function testSet(array $samples): string
{
if (!is_array($samples[0])) {
$samples = [$samples];
}
$set = '';
foreach ($samples as $sample) {
$set .= sprintf('0 %s %s', self::sampleRow($sample), PHP_EOL);
}
return $set;
}
/**
* @param string $rawPredictions
* @param array $labels
*
* @return array
*/
public static function predictions(string $rawPredictions, array $labels): array
{
$numericLabels = self::numericLabels($labels);
$results = [];
foreach (explode(PHP_EOL, $rawPredictions) as $result) {
if (strlen($result) > 0) {
$results[] = array_search($result, $numericLabels);
}
}
return $results;
}
/**
* @param array $labels
*
* @return array
*/
public static function numericLabels(array $labels): array
{
$numericLabels = [];
foreach ($labels as $label) {
if (isset($numericLabels[$label])) {
continue;
}
$numericLabels[$label] = count($numericLabels);
}
return $numericLabels;
}
/**
* @param array $sample
*
* @return string
*/
private static function sampleRow(array $sample): string
{
$row = [];
foreach ($sample as $index => $feature) {
$row[] = sprintf('%s:%s', $index + 1, $feature);
}
return implode(' ', $row);
}
}
lib/mlbackend/php/phpml/src/Phpml/SupportVectorMachine/Kernel.php
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<?php
declare(strict_types=1);
namespace Phpml\SupportVectorMachine;
abstract class Kernel
{
/**
* u'*v.
*/
const LINEAR = 0;
/**
* (gamma*u'*v + coef0)^degree.
*/
const POLYNOMIAL = 1;
/**
* exp(-gamma*|u-v|^2).
*/
const RBF = 2;
/**
* tanh(gamma*u'*v + coef0).
*/
const SIGMOID = 3;
}
lib/mlbackend/php/phpml/src/Phpml/SupportVectorMachine/SupportVectorMachine.php
+239
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<?php
declare(strict_types=1);
namespace Phpml\SupportVectorMachine;
use Phpml\Helper\Trainable;
class SupportVectorMachine
{
use Trainable;
/**
* @var int
*/
private $type;
/**
* @var int
*/
private $kernel;
/**
* @var float
*/
private $cost;
/**
* @var float
*/
private $nu;
/**
* @var int
*/
private $degree;
/**
* @var float
*/
private $gamma;
/**
* @var float
*/
private $coef0;
/**
* @var float
*/
private $epsilon;
/**
* @var float
*/
private $tolerance;
/**
* @var int
*/
private $cacheSize;
/**
* @var bool
*/
private $shrinking;
/**
* @var bool
*/
private $probabilityEstimates;
/**
* @var string
*/
private $binPath;
/**
* @var string
*/
private $varPath;
/**
* @var string
*/
private $model;
/**
* @var array
*/
private $targets = [];
/**
* @param int $type
* @param int $kernel
* @param float $cost
* @param float $nu
* @param int $degree
* @param float|null $gamma
* @param float $coef0
* @param float $epsilon
* @param float $tolerance
* @param int $cacheSize
* @param bool $shrinking
* @param bool $probabilityEstimates
*/
public function __construct(
int $type, int $kernel, float $cost = 1.0, float $nu = 0.5, int $degree = 3,
float $gamma = null, float $coef0 = 0.0, float $epsilon = 0.1, float $tolerance = 0.001,
int $cacheSize = 100, bool $shrinking = true, bool $probabilityEstimates = false
) {
$this->type = $type;
$this->kernel = $kernel;
$this->cost = $cost;
$this->nu = $nu;
$this->degree = $degree;
$this->gamma = $gamma;
$this->coef0 = $coef0;
$this->epsilon = $epsilon;
$this->tolerance = $tolerance;
$this->cacheSize = $cacheSize;
$this->shrinking = $shrinking;
$this->probabilityEstimates = $probabilityEstimates;
$rootPath = realpath(implode(DIRECTORY_SEPARATOR, [__DIR__, '..', '..', '..'])).DIRECTORY_SEPARATOR;
$this->binPath = $rootPath.'bin'.DIRECTORY_SEPARATOR.'libsvm'.DIRECTORY_SEPARATOR;
$this->varPath = $rootPath.'var'.DIRECTORY_SEPARATOR;
}
/**
* @param array $samples
* @param array $targets
*/
public function train(array $samples, array $targets)
{
$this->samples = array_merge($this->samples, $samples);
$this->targets = array_merge($this->targets, $targets);
$trainingSet = DataTransformer::trainingSet($this->samples, $this->targets, in_array($this->type, [Type::EPSILON_SVR, Type::NU_SVR]));
file_put_contents($trainingSetFileName = $this->varPath.uniqid('phpml', true), $trainingSet);
$modelFileName = $trainingSetFileName.'-model';
$command = $this->buildTrainCommand($trainingSetFileName, $modelFileName);
$output = '';
exec(escapeshellcmd($command), $output);
$this->model = file_get_contents($modelFileName);
unlink($trainingSetFileName);
unlink($modelFileName);
}
/**
* @return string
*/
public function getModel()
{
return $this->model;
}
/**
* @param array $samples
*
* @return array
*/
public function predict(array $samples)
{
$testSet = DataTransformer::testSet($samples);
file_put_contents($testSetFileName = $this->varPath.uniqid('phpml', true), $testSet);
file_put_contents($modelFileName = $testSetFileName.'-model', $this->model);
$outputFileName = $testSetFileName.'-output';
$command = sprintf('%ssvm-predict%s %s %s %s', $this->binPath, $this->getOSExtension(), $testSetFileName, $modelFileName, $outputFileName);
$output = '';
exec(escapeshellcmd($command), $output);
$predictions = file_get_contents($outputFileName);
unlink($testSetFileName);
unlink($modelFileName);
unlink($outputFileName);
if (in_array($this->type, [Type::C_SVC, Type::NU_SVC])) {
$predictions = DataTransformer::predictions($predictions, $this->targets);
} else {
$predictions = explode(PHP_EOL, trim($predictions));
}
if (!is_array($samples[0])) {
return $predictions[0];
}
return $predictions;
}
/**
* @return string
*/
private function getOSExtension()
{
$os = strtoupper(substr(PHP_OS, 0, 3));
if ($os === 'WIN') {
return '.exe';
} elseif ($os === 'DAR') {
return '-osx';
}
return '';
}
/**
* @param $trainingSetFileName
* @param $modelFileName
*
* @return string
*/
private function buildTrainCommand(string $trainingSetFileName, string $modelFileName): string
{
return sprintf('%ssvm-train%s -s %s -t %s -c %s -n %s -d %s%s -r %s -p %s -m %s -e %s -h %d -b %d %s %s',
$this->binPath,
$this->getOSExtension(),
$this->type,
$this->kernel,
$this->cost,
$this->nu,
$this->degree,
$this->gamma !== null ? ' -g '.$this->gamma : '',
$this->coef0,
$this->epsilon,
$this->cacheSize,
$this->tolerance,
$this->shrinking,
$this->probabilityEstimates,
escapeshellarg($trainingSetFileName),
escapeshellarg($modelFileName)
);
}
}
lib/mlbackend/php/phpml/src/Phpml/SupportVectorMachine/Type.php
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<?php
declare(strict_types=1);
namespace Phpml\SupportVectorMachine;
abstract class Type
{
/**
* classification.
*/
const C_SVC = 0;
/**
* classification.
*/
const NU_SVC = 1;
/**
* distribution estimation.
*/
const ONE_CLASS_SVM = 2;
/**
* regression.
*/
const EPSILON_SVR = 3;
/**
* regression.
*/
const NU_SVR = 4;
}