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<?php |
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declare(strict_types=1); |
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namespace Phpml\Regression; |
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use Phpml\Helper\Predictable; |
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use Phpml\Math\Matrix; |
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class LeastSquares implements Regression |
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{ |
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use Predictable; |
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/** |
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* @var array |
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*/ |
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private $samples = []; |
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/** |
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* @var array |
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*/ |
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private $targets = []; |
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/** |
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* @var float |
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*/ |
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private $intercept; |
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/** |
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* @var array |
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*/ |
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private $coefficients = []; |
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public function train(array $samples, array $targets): void |
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{ |
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$this->samples = array_merge($this->samples, $samples); |
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$this->targets = array_merge($this->targets, $targets); |
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$this->computeCoefficients(); |
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} |
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/** |
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* @return mixed |
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*/ |
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public function predictSample(array $sample) |
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{ |
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$result = $this->intercept; |
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foreach ($this->coefficients as $index => $coefficient) { |
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$result += $coefficient * $sample[$index]; |
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} |
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return $result; |
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} |
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public function getCoefficients(): array |
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{ |
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return $this->coefficients; |
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} |
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public function getIntercept(): float |
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{ |
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return $this->intercept; |
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} |
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/** |
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* coefficient(b) = (X'X)-1X'Y. |
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*/ |
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private function computeCoefficients(): void |
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{ |
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$samplesMatrix = $this->getSamplesMatrix(); |
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$targetsMatrix = $this->getTargetsMatrix(); |
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$ts = $samplesMatrix->transpose()->multiply($samplesMatrix)->inverse(); |
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$tf = $samplesMatrix->transpose()->multiply($targetsMatrix); |
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$this->coefficients = $ts->multiply($tf)->getColumnValues(0); |
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$this->intercept = array_shift($this->coefficients); |
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} |
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/** |
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* Add one dimension for intercept calculation. |
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*/ |
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private function getSamplesMatrix(): Matrix |
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{ |
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$samples = []; |
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foreach ($this->samples as $sample) { |
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array_unshift($sample, 1); |
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$samples[] = $sample; |
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} |
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return new Matrix($samples); |
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} |
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private function getTargetsMatrix(): Matrix |
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{ |
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if (is_array($this->targets[0])) { |
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return new Matrix($this->targets); |
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} |
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return Matrix::fromFlatArray($this->targets); |
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} |
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} |
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php-ai /
php-ml
