# PHP-ML - Machine Learning library for PHP [![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.0-8892BF.svg)](https://php.net/) [![Latest Stable Version](https://img.shields.io/packagist/v/php-ai/php-ml.svg)](https://packagist.org/packages/php-ai/php-ml) [![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) ![PHP-ML - Machine Learning library for PHP](assets/php-ml-logo.png) Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Preprocessing, Feature Extraction and much more in one library. PHP-ML requires PHP >= 7.0. 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 ``` ## Examples Example scripts are available in a separate repository [php-ai/php-ml-examples](https://github.com/php-ai/php-ml-examples). ## Features * Association rule Lerning * [Apriori](machine-learning/association/apriori/) * Classification * [SVC](machine-learning/classification/svc/) * [k-Nearest Neighbors](machine-learning/classification/k-nearest-neighbors/) * [Naive Bayes](machine-learning/classification/naive-bayes/) * Regression * [Least Squares](machine-learning/regression/least-squares/) * [SVR](machine-learning/regression/svr/) * Clustering * [k-Means](machine-learning/clustering/k-means/) * [DBSCAN](machine-learning/clustering/dbscan/) * Metric * [Accuracy](machine-learning/metric/accuracy/) * [Confusion Matrix](machine-learning/metric/confusion-matrix/) * [Classification Report](machine-learning/metric/classification-report/) * Workflow * [Pipeline](machine-learning/workflow/pipeline) * Neural Network * [Multilayer Perceptron Classifier](machine-learning/neural-network/multilayer-perceptron-classifier/) * Cross Validation * [Random Split](machine-learning/cross-validation/random-split/) * [Stratified Random Split](machine-learning/cross-validation/stratified-random-split/) * Preprocessing * [Normalization](machine-learning/preprocessing/normalization/) * [Imputation missing values](machine-learning/preprocessing/imputation-missing-values/) * Feature Extraction * [Token Count Vectorizer](machine-learning/feature-extraction/token-count-vectorizer/) * [Tf-idf Transformer](machine-learning/feature-extraction/tf-idf-transformer/) * Datasets * [Array](machine-learning/datasets/array-dataset/) * [CSV](machine-learning/datasets/csv-dataset/) * [Files](machine-learning/datasets/files-dataset/) * Ready to use: * [Iris](machine-learning/datasets/demo/iris/) * [Wine](machine-learning/datasets/demo/wine/) * [Glass](machine-learning/datasets/demo/glass/) * Models management * [Persistency](machine-learning/model-manager/persistency/) * Math * [Distance](math/distance/) * [Matrix](math/matrix/) * [Set](math/set/) * [Statistic](math/statistic/) ## Contribute - Issue Tracker: github.com/php-ai/php-ml/issues - Source Code: github.com/php-ai/php-ml You can find more about contributing in [CONTRIBUTING.md](CONTRIBUTING.md). ## License PHP-ML is released under the MIT Licence. See the bundled LICENSE file for details. ## Author Arkadiusz Kondas (@ArkadiuszKondas)