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<?php |
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declare(strict_types=1); |
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namespace Phpml\Classification; |
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use Phpml\Classification\Classifier; |
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use Phpml\Exception\InvalidArgumentException; |
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use Phpml\NeuralNetwork\Network\MultilayerPerceptron; |
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use Phpml\NeuralNetwork\Training\Backpropagation; |
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use Phpml\NeuralNetwork\ActivationFunction; |
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use Phpml\NeuralNetwork\Layer; |
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use Phpml\NeuralNetwork\Node\Bias; |
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use Phpml\NeuralNetwork\Node\Input; |
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use Phpml\NeuralNetwork\Node\Neuron; |
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use Phpml\NeuralNetwork\Node\Neuron\Synapse; |
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use Phpml\Helper\Predictable; |
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class MLPClassifier extends MultilayerPerceptron implements Classifier |
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{ |
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/** |
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* @param mixed $target |
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* @return int |
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*/ |
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public function getTargetClass($target): int |
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{ |
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if (!in_array($target, $this->classes)) { |
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throw InvalidArgumentException::invalidTarget($target); |
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} |
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return array_search($target, $this->classes); |
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} |
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/** |
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* @param array $sample |
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* |
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* @return mixed |
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*/ |
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protected function predictSample(array $sample) |
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{ |
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$output = $this->setInput($sample)->getOutput(); |
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$predictedClass = null; |
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$max = 0; |
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foreach ($output as $class => $value) { |
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if ($value > $max) { |
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$predictedClass = $class; |
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$max = $value; |
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} |
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} |
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return $this->classes[$predictedClass]; |
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} |
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/** |
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* @param array $sample |
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* @param mixed $target |
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*/ |
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protected function trainSample(array $sample, $target) |
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{ |
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// Feed-forward. |
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$this->setInput($sample)->getOutput(); |
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// Back-propagate. |
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$this->backpropagation->backpropagate($this->getLayers(), $this->getTargetClass($target)); |
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} |
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} |
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php-ai /
php-ml
