perceptron.php

<?php

class MatrixMath {
    public static function dotVectors($vector1, $vector2)
    {
        $total = 0;
        $dim = count($vector1);
        for ($i = 0; $i < $dim; $i++) {
            $total += $vector1[$i] * $vector2[$i];
        }
        return $total;
    }
}

class PerceptronBase  {
    protected $bias;
    protected $learningRate;
    protected $errorSum = 0;
    protected $iterationError = 0;

    public function getBias()
    {
        return $this->bias;
    }

    public function setBias($bias)
    {
        if (!is_numeric($bias)) {
            throw new \InvalidArgumentException();
        }
        $this->bias = $bias;
    }

    public function getLearningRate()
    {
        return $this->learningRate;
    }

    public function setLearningRate($learningRate)
    {
        $this->learningRate = $learningRate;
    }

    public function getIterationError()
    {
        return $this->iterationError;
    }

}

class Perceptron extends PerceptronBase
{
    protected $tailleDesFeatures;
    protected $listeDesCoeff;

    protected $activation = null;

    //, $bias = 0.0)//, $learningRate = .5)
    public function __construct($listeDesFeatures)
    {
        $this->tailleDesFeatures = $listeDesFeatures;
        for ($i = 0; $i < $this->tailleDesFeatures; $i++) {
            $this->listeDesCoeff[$i] = rand()/getrandmax() * 2 - 1;
        }
    }
    //$this->bias = $bias;
    //$this->learningRate = $learningRate;

    public function test($listeDesFeatures)
    {
        $regression = MatrixMath::dotVectors($this->listeDesCoeff, $listeDesFeatures);// + $this->bias;
        // Activation function
        $this->activation = $regression > 0 ? 1 : 0;
        return $this->activation;
    }

    public function train($listeDesFeature, $bonneResponseAttendue)
    {
        $this->iterations += 1;
        $regression = $this->test($listeDesFeature);
        for ($i = 0; $i < $this->tailleDesFeatures; $i++) {
            $this->listeDesCoeff[$i] =
                $this->listeDesCoeff[$i] + ((int) $bonneResponseAttendue - (int) $regression) * $listeDesFeature[$i] /* * $this->learningRate */;
        }
    }
    //$this->bias = $this->bias + ((int) $outcome - (int) $output);
    //$this->errorSum += (int) $outcome - (int) $output;
    //$this->iterationError = 1 / $this->iterations * $this->errorSum;

    protected $iterations = 0;

    public function getActivation()
    {
        if(is_null($this->activation))
        {
            throw new \RuntimeException();
        }
        else
        {
            return $this->activation;
        }
    }

    public function getListeDesCoeff()
    {
        return $this->listeDesCoeff;
    }

    public function setListeDesCoeff($listeDesCoeff)
    {
        $this->listeDesCoeff = $listeDesCoeff;
    }

}