https://github.com/denissimon/prediction-builder

A library for machine learning that builds predictions using a linear regression.
https://github.com/denissimon/prediction-builder

composer linear-regression machine-learning ml php prediction regression

Last synced: 5 days ago
JSON representation

A library for machine learning that builds predictions using a linear regression.

• Host: GitHub
• URL: https://github.com/denissimon/prediction-builder
• Owner: denissimon
• License: mit
• Created: 2015-06-08T16:52:27.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2024-11-14T05:51:19.000Z (3 months ago)
• Last Synced: 2025-01-15T04:35:17.163Z (19 days ago)
• Topics: composer, linear-regression, machine-learning, ml, php, prediction, regression
• Language: PHP
• Homepage:
• Size: 9.77 KB
• Stars: 112
• Watchers: 8
• Forks: 13
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
PredictionBuilder

=================

[![Latest Stable Version](https://poser.pugx.org/denissimon/prediction-builder/v/stable.svg)](https://packagist.org/packages/denissimon/prediction-builder)

[![Total Downloads](https://poser.pugx.org/denissimon/prediction-builder/downloads)](https://packagist.org/packages/denissimon/prediction-builder)

[![License](https://poser.pugx.org/denissimon/prediction-builder/license.svg)](https://github.com/denissimon/prediction-builder/blob/master/LICENSE)

PredictionBuilder is a library for machine learning that builds predictions using a linear regression.

Requirements

------------

This project requires [PHP 5.4 or higher](http://php.net) because makes use of trait and short array syntax.

Installation

------------

You can install the library by [Composer](https://getcomposer.org). Add this to your project's composer.json:

``` json

"require": {

    "denissimon/prediction-builder": "*"

}

```

Then run `php composer.phar install` (or `composer install`).

Example

-------

``` php

use PredictionBuilder\PredictionBuilder;

require_once __DIR__ . '/vendor/autoload.php';

$data = [[1,20],[2,70],[2,45],[3,81],[5,73],[6,80],[7,110]];

$x = 4.5;

// What is the expected y value for a given x value?

try {

    $prediction = new PredictionBuilder($x, $data);

    $result = $prediction->build(); // y = 76.65

} catch (\Exception $e) {

    echo $e->getMessage(), "\n";

}

```

The returned object has the following properties:

`$result->ln_model` linear model that fits the data: "29.56362+10.46364x"

`$result->cor` correlation coefficient: 0.8348

`$result->x` given x value: 4.5

`$result->y` predicted y value: 76.65

License

-------

Licensed under the [MIT License](https://github.com/denissimon/prediction-builder/blob/master/LICENSE)