1 <?php 2 3 declare(strict_types=1); 4 5 namespace Phpml\Regression; 6 7 use Phpml\Helper\Predictable; 8 use Phpml\Math\Matrix; 9 10 class LeastSquares implements Regression 11 { 12 use Predictable; 13 14 /** 15 * @var array 16 */ 17 private $samples = []; 18 19 /** 20 * @var array 21 */ 22 private $targets = []; 23 24 /** 25 * @var float 26 */ 27 private $intercept; 28 29 /** 30 * @var array 31 */ 32 private $coefficients = []; 33 34 public function train(array $samples, array $targets): void 35 { 36 $this->samples = array_merge($this->samples, $samples); 37 $this->targets = array_merge($this->targets, $targets); 38 39 $this->computeCoefficients(); 40 } 41 42 /** 43 * @return mixed 44 */ 45 public function predictSample(array $sample) 46 { 47 $result = $this->intercept; 48 foreach ($this->coefficients as $index => $coefficient) { 49 $result += $coefficient * $sample[$index]; 50 } 51 52 return $result; 53 } 54 55 public function getCoefficients(): array 56 { 57 return $this->coefficients; 58 } 59 60 public function getIntercept(): float 61 { 62 return $this->intercept; 63 } 64 65 /** 66 * coefficient(b) = (X'X)-1X'Y. 67 */ 68 private function computeCoefficients(): void 69 { 70 $samplesMatrix = $this->getSamplesMatrix(); 71 $targetsMatrix = $this->getTargetsMatrix(); 72 73 $ts = $samplesMatrix->transpose()->multiply($samplesMatrix)->inverse(); 74 $tf = $samplesMatrix->transpose()->multiply($targetsMatrix); 75 76 $this->coefficients = $ts->multiply($tf)->getColumnValues(0); 77 $this->intercept = array_shift($this->coefficients); 78 } 79 80 /** 81 * Add one dimension for intercept calculation. 82 */ 83 private function getSamplesMatrix(): Matrix 84 { 85 $samples = []; 86 foreach ($this->samples as $sample) { 87 array_unshift($sample, 1); 88 $samples[] = $sample; 89 } 90 91 return new Matrix($samples); 92 } 93 94 private function getTargetsMatrix(): Matrix 95 { 96 if (is_array($this->targets[0])) { 97 return new Matrix($this->targets); 98 } 99 100 return Matrix::fromFlatArray($this->targets); 101 } 102 }
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