mirror of
https://github.com/Llewellynvdm/php-ml.git
synced 2024-11-29 16:24:05 +00:00
76 lines
2.9 KiB
Markdown
76 lines
2.9 KiB
Markdown
# PHP-ML - Machine Learning library for PHP
|
|
|
|
[![Build Status](https://scrutinizer-ci.com/g/php-ai/php-ml/badges/build.png?b=develop)](https://scrutinizer-ci.com/g/php-ai/php-ml/build-status/develop)
|
|
[![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=develop)](http://php-ml.readthedocs.org/en/develop/?badge=develop)
|
|
[![Total Downloads](https://poser.pugx.org/php-ai/php-ml/downloads.svg)](https://packagist.org/packages/php-ai/php-ml)
|
|
[![License](https://poser.pugx.org/php-ai/php-ml/license.svg)](https://packagist.org/packages/php-ai/php-ml)
|
|
[![Scrutinizer Code Quality](https://scrutinizer-ci.com/g/php-ai/php-ml/badges/quality-score.png?b=develop)](https://scrutinizer-ci.com/g/php-ai/php-ml/?branch=develop)
|
|
|
|
Fresh approach to Machine Learning in PHP. Note that at the moment PHP is not the best choice for machine learning but maybe this will change ...
|
|
|
|
Simple example of classification:
|
|
```php
|
|
use Phpml\Classification\KNearestNeighbors;
|
|
|
|
$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
|
|
$labels = ['a', 'a', 'a', 'b', 'b', 'b'];
|
|
|
|
$classifier = new KNearestNeighbors();
|
|
$classifier->train($samples, $labels);
|
|
|
|
$classifier->predict([3, 2]);
|
|
// return 'b'
|
|
```
|
|
|
|
## Documentation
|
|
|
|
To find out how to use PHP-ML follow [Documentation](http://php-ml.readthedocs.org/).
|
|
|
|
## Installation
|
|
|
|
Currently this library is in the process of developing, but You can install it with Composer:
|
|
|
|
```
|
|
composer require php-ai/php-ml
|
|
```
|
|
|
|
## Features
|
|
|
|
* Classification
|
|
* [k-Nearest Neighbors](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/k-nearest-neighbors/)
|
|
* [Naive Bayes](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/naive-bayes/)
|
|
* Regression
|
|
* [Least Squares](http://php-ml.readthedocs.io/en/latest/machine-learning/regression/least-squares/)
|
|
* Clustering
|
|
* [k-Means](http://php-ml.readthedocs.io/en/latest/machine-learning/clustering/k-means)
|
|
* [DBSCAN](http://php-ml.readthedocs.io/en/latest/machine-learning/clustering/dbscan)
|
|
* Cross Validation
|
|
* [Random Split](http://php-ml.readthedocs.io/en/latest/machine-learning/cross-validation/random-split)
|
|
* Datasets
|
|
* [CSV](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/csv-dataset)
|
|
* Ready to use:
|
|
* [Iris](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/demo/iris/)
|
|
* Math
|
|
* [Distance](http://php-ml.readthedocs.io/en/latest/math/distance/)
|
|
* [Matrix](http://php-ml.readthedocs.io/en/latest/math/matrix/)
|
|
|
|
|
|
## Contribute
|
|
|
|
- Issue Tracker: github.com/php-ai/php-ml/issues
|
|
- Source Code: github.com/php-ai/php-ml
|
|
|
|
After installation, you can launch the test suite in project root directory (you will need to install dev requirements with Composer)
|
|
|
|
```
|
|
bin/phpunit
|
|
```
|
|
|
|
## License
|
|
|
|
PHP-ML is released under the MIT Licence. See the bundled LICENSE file for details.
|
|
|
|
## Author
|
|
|
|
Arkadiusz Kondas (@ArkadiuszKondas)
|