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better arguments format for regression

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This commit is contained in:
Arkadiusz Kondas 2016-04-30 13:54:01 +02:00
parent b1c47d5e9d
commit ff79de7e14
3 changed files with 55 additions and 14 deletions
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25
src/Phpml/Math/Matrix.php
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@ -51,6 +51,21 @@ class Matrix
$this->matrix = $matrix;
}
/**
* @param array $array
*
* @return Matrix
*/
public static function fromFlatArray(array $array)
{
$matrix = [];
foreach ($array as $value) {
$matrix[] = [$value];
}
return new self($matrix);
}
/**
* @return array
*/
@ -115,16 +130,14 @@ class Matrix
if ($this->rows == 1 && $this->columns == 1) {
$determinant = $this->matrix[0][0];
} elseif ($this->rows == 2 && $this->columns == 2) {
$determinant = $this->matrix[0][0] * $this->matrix[1][1] -
$determinant =
$this->matrix[0][0] * $this->matrix[1][1] -
$this->matrix[0][1] * $this->matrix[1][0];
} else {
for ($j = 0; $j < $this->columns; ++$j) {
$subMatrix = $this->crossOut(0, $j);
if (fmod($j, 2) == 0) {
$determinant += $this->matrix[0][$j] * $subMatrix->getDeterminant();
} else {
$determinant -= $this->matrix[0][$j] * $subMatrix->getDeterminant();
}
$minor = $this->matrix[0][$j] * $subMatrix->getDeterminant();
$determinant += fmod($j, 2) == 0 ? $minor : -$minor;
}
}

32
src/Phpml/Regression/LeastSquares.php
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@ -76,8 +76,8 @@ class LeastSquares implements Regression
*/
private function computeCoefficients()
{
$samplesMatrix = new Matrix($this->samples);
$targetsMatrix = new Matrix($this->targets);
$samplesMatrix = $this->getSamplesMatrix();
$targetsMatrix = $this->getTargetsMatrix();
$ts = $samplesMatrix->transpose()->multiply($samplesMatrix)->inverse();
$tf = $samplesMatrix->transpose()->multiply($targetsMatrix);
@ -85,4 +85,32 @@ class LeastSquares implements Regression
$this->coefficients = $ts->multiply($tf)->getColumnValues(0);
$this->intercept = array_shift($this->coefficients);
}
/**
* Add one dimension for intercept calculation.
*
* @return Matrix
*/
private function getSamplesMatrix()
{
$samples = [];
foreach ($this->samples as $sample) {
array_unshift($sample, 1);
$samples[] = $sample;
}
return new Matrix($samples);
}
/**
* @return Matrix
*/
private function getTargetsMatrix()
{
if (is_array($this->targets[0])) {
return new Matrix($this->targets);
}
return Matrix::fromFlatArray($this->targets);
}
}

12
tests/Phpml/Regression/LeastSquaresTest.php
View File

@ -13,8 +13,8 @@ class LeastSquaresTest extends \PHPUnit_Framework_TestCase
$delta = 0.01;
//https://www.easycalculation.com/analytical/learn-least-square-regression.php
$samples = [[1, 60], [1, 61], [1, 62], [1, 63], [1, 65]];
$targets = [[3.1], [3.6], [3.8], [4], [4.1]];
$samples = [[60], [61], [62], [63], [65]];
$targets = [3.1, 3.6, 3.8, 4, 4.1];
$regression = new LeastSquares();
$regression->train($samples, $targets);
@ -22,8 +22,8 @@ class LeastSquaresTest extends \PHPUnit_Framework_TestCase
$this->assertEquals(4.06, $regression->predict([64]), '', $delta);
//http://www.stat.wmich.edu/s216/book/node127.html
$samples = [[1, 9300], [1, 10565], [1, 15000], [1, 15000], [1, 17764], [1, 57000], [1, 65940], [1, 73676], [1, 77006], [1, 93739], [1, 146088], [1, 153260]];
$targets = [[7100], [15500], [4400], [4400], [5900], [4600], [8800], [2000], [2750], [2550], [960], [1025]];
$samples = [[9300], [10565], [15000], [15000], [17764], [57000], [65940], [73676], [77006], [93739], [146088], [153260]];
$targets = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
$regression = new LeastSquares();
$regression->train($samples, $targets);
@ -40,8 +40,8 @@ class LeastSquaresTest extends \PHPUnit_Framework_TestCase
$delta = 0.01;
//http://www.stat.wmich.edu/s216/book/node129.html
$samples = [[1, 73676, 1996], [1, 77006, 1998], [1, 10565, 2000], [1, 146088, 1995], [1, 15000, 2001], [1, 65940, 2000], [1, 9300, 2000], [1, 93739, 1996], [1, 153260, 1994], [1, 17764, 2002], [1, 57000, 1998], [1, 15000, 2000]];
$targets = [[2000], [2750], [15500], [960], [4400], [8800], [7100], [2550], [1025], [5900], [4600], [4400]];
$samples = [[73676, 1996], [77006, 1998], [10565, 2000], [146088, 1995], [15000, 2001], [65940, 2000], [9300, 2000], [93739, 1996], [153260, 1994], [17764, 2002], [57000, 1998], [15000, 2000]];
$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
$regression = new LeastSquares();
$regression->train($samples, $targets);