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Building Machine Learning Models with PHP: Practical Guide and Examples

M66 2025-06-24

How to Build Machine Learning Models Using PHP

Machine learning, as a key branch of artificial intelligence, is widely applied across various fields. When building machine learning models, PHP—a popular server-side programming language—can also play a significant role. This article will introduce how to use PHP to build machine learning models and provide practical code examples.

1. Installing PHP Machine Learning Libraries

Before starting to build machine learning models, you need to install related PHP machine learning libraries. PHP-ML is a comprehensive PHP machine learning library that supports regression, classification, clustering, and more. Below are the steps to install PHP-ML:

  1. Open the terminal and install Composer (PHP’s dependency manager):
$ curl -sS https://getcomposer.org/installer | php
$ mv composer.phar /usr/local/bin/composer
  1. Create a composer.json file in your PHP project folder with the following content:
{
  "require": {
    "php-ai/php-ml": "~0.8"
  }
}
  1. Run the command below to install the PHP-ML library:
$ composer install

2. Regression Model

Regression models are commonly used to predict continuous target variables. Below is an example demonstrating how to build a regression model using PHP:

// Include necessary classes
require 'vendor/autoload.php';
<p>use Phpml\Regression\SVR;<br>
use Phpml\SupportVectorMachine\Kernel;</p>
<p>// Training data<br>
$samples = [[60], [61], [62], [63], [65]];<br>
$targets = [3.1, 3.6, 3.8, 4, 4.1];</p>
<p>// Create regression model<br>
$regression = new SVR(Kernel::LINEAR);<br>
$regression->train($samples, $targets);</p>
<p>// Predict new data<br>
$prediction = $regression->predict([[64]]);<br>
echo "Prediction result: " . $prediction;<br>

3. Classification Model

Classification models are used to categorize samples into different classes. The example below shows how to build a classification model with PHP:

// Include necessary classes
require 'vendor/autoload.php';
<p>use Phpml\Classification\SVC;<br>
use Phpml\SupportVectorMachine\Kernel;</p>
<p>// Training data<br>
$samples = [[150, 50], [160, 60], [170, 70], [180, 80]];<br>
$targets = ['Male', 'Female', 'Male', 'Female'];</p>
<p>// Create classification model<br>
$classifier = new SVC(Kernel::RBF, 1000);<br>
$classifier->train($samples, $targets);</p>
<p>// Predict new data<br>
$prediction = $classifier->predict([[190, 90]]);<br>
echo "Prediction result: " . $prediction;<br>

4. Clustering Model

Clustering models group samples into different clusters. Below is an example showing how to build a clustering model using PHP:

// Include necessary classes
require 'vendor/autoload.php';
<p>use Phpml\Clustering\KMeans;</p>
<p>// Training data<br>
$samples = [[60], [61], [62], [63], [65]];</p>
<p>// Create clustering model<br>
$clustering = new KMeans(3);<br>
$clustering->train($samples);</p>
<p>// Predict new data<br>
$prediction = $clustering->predict([[64]]);<br>
echo "Prediction result: " . $prediction;<br>

Summary

This article introduced the basic process of building machine learning models with PHP and demonstrated implementations for regression, classification, and clustering models with practical examples. Besides PHP-ML, there are other machine learning libraries in the PHP ecosystem that developers can choose from based on project requirements. We hope this article helps you successfully develop machine learning projects in PHP.

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