Linear Regression with PHP

Multiple Linear Regression with PHP-ML

Involves two or more independent variables. For example, predicting house prices based on factors like size, number of rooms, and location. This involves more than one independent variable and one dependent variable. The equation for multiple linear regression is: $y = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \dots + \beta_n x_n$

Dataset


                        
rooms,size,distance,price
1,500,8,157250
2,750,9,198500
2,700,7,207825
2,850,6,251175
2,900,5,276250
3,1150,6,327250
3,1200,4,374850
3,1350,5,368750
3,1250,5,382500
3,1300,3,425000
4,1500,4,442750
4,1600,3,493000
4,1650,2,531250
4,1700,3,535500
4,1800,3,545000
5,1900,2,612000
5,2000,1,657750
5,2050,2,663000
5,2150,2,678250
5,2100,1,701500
6,2300,2,742750
6,2400,1,786250
6,2450,2,807500
6,2500,1,850000
6,2550,1,862500

Example of use:


<?php

use Phpml\Dataset\ArrayDataset;
use Phpml\Dataset\CsvDataset;
use Phpml\Metric\Regression;
use Phpml\Regression\LeastSquares;

// Load the raw data from CSV
$dataset = new CsvDataset(dirname(__FILE__) . '/data/houses2.csv', 3, true);

$samples = $dataset->getSamples();
$labels = $dataset->getTargets();

$regressor = new LeastSquares();
$regressor->train($samples, $labels);

$newSamples = [
    [4, 1800, 3],
    [2, 1200, 8],
];

$predictions = $regressor->predict($newSamples);

// Print predictions
echo "Predictions for new houses:\n";
echo "--------------------------\n";
foreach ($predictions as $index => $prediction) {
    echo sprintf(
        "House %d: $%s\n",
        $index + 1,
        number_format($prediction, 2)
    );
}

// Calculate error metrics for actual values
$actualValues = [450000, 280000];

// Calculate error metrics for actual values
echo "\n\nMetrics:";
echo "\n-------";
$mse = Regression::meanSquaredError($predictions, $actualValues);
echo "\nMean Squared Error: $" . number_format($mse, 2);
echo "\nRoot Mean Squared Error: $" . number_format(sqrt($mse), 2);

$mae = Regression::meanAbsoluteError($predictions, $actualValues);
echo "\nMean Absolute Error: $" . number_format(abs($mae), 2);