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📄 Accuracy.php(770 B)
📄 ClassificationReport.php(5.76 KB)
📄 ConfusionMatrix.php(1.3 KB)
📄 Regression.php(2.38 KB)

Editing: Regression.php

<?php

declare(strict_types=1);

namespace Phpml\Metric;

use Phpml\Exception\InvalidArgumentException;
use Phpml\Math\Statistic\Correlation;
use Phpml\Math\Statistic\Mean;

final class Regression
{
    public static function meanSquaredError(array $targets, array $predictions): float
    {
        self::assertCountEquals($targets, $predictions);

$errors = [];
        foreach ($targets as $index => $target) {
            $errors[] = (($target - $predictions[$index]) ** 2);
        }

return Mean::arithmetic($errors);
    }

public static function meanSquaredLogarithmicError(array $targets, array $predictions): float
    {
        self::assertCountEquals($targets, $predictions);

$errors = [];
        foreach ($targets as $index => $target) {
            $errors[] = log((1 + $target) / (1 + $predictions[$index])) ** 2;
        }

return Mean::arithmetic($errors);
    }

public static function meanAbsoluteError(array $targets, array $predictions): float
    {
        self::assertCountEquals($targets, $predictions);

$errors = [];
        foreach ($targets as $index => $target) {
            $errors[] = abs($target - $predictions[$index]);
        }

return Mean::arithmetic($errors);
    }

public static function medianAbsoluteError(array $targets, array $predictions): float
    {
        self::assertCountEquals($targets, $predictions);

$errors = [];
        foreach ($targets as $index => $target) {
            $errors[] = abs($target - $predictions[$index]);
        }

return (float) Mean::median($errors);
    }

public static function r2Score(array $targets, array $predictions): float
    {
        self::assertCountEquals($targets, $predictions);

return Correlation::pearson($targets, $predictions) ** 2;
    }

public static function maxError(array $targets, array $predictions): float
    {
        self::assertCountEquals($targets, $predictions);

$errors = [];
        foreach ($targets as $index => $target) {
            $errors[] = abs($target - $predictions[$index]);
        }

return (float) max($errors);
    }

private static function assertCountEquals(array &$targets, array &$predictions): void
    {
        if (count($targets) !== count($predictions)) {
            throw new InvalidArgumentException('Targets count must be equal with predictions count');
        }
    }
}

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