# PHP-ML - Machine Learning library for PHP [![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.1-8892BF.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://travis-ci.org/php-ai/php-ml.svg?branch=master)](https://travis-ci.org/php-ai/php-ml) [![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=master)](http://php-ml.readthedocs.org/) [![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) [![Coverage Status](https://coveralls.io/repos/github/php-ai/php-ml/badge.svg?branch=master)](https://coveralls.io/github/php-ai/php-ml?branch=master) [![Scrutinizer Code Quality](https://scrutinizer-ci.com/g/php-ai/php-ml/badges/quality-score.png?b=master)](https://scrutinizer-ci.com/g/php-ai/php-ml/?branch=master)

Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library. PHP-ML requires PHP >= 7.1. Simple example of classification: ```php require_once __DIR__ . '/vendor/autoload.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' ``` ## Awards ## 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.md) * Classification * [SVC](machine-learning/classification/svc.md) * [k-Nearest Neighbors](machine-learning/classification/k-nearest-neighbors.md) * [Naive Bayes](machine-learning/classification/naive-bayes.md) * Regression * [Least Squares](machine-learning/regression/least-squares.md) * [SVR](machine-learning/regression/svr.md) * Clustering * [k-Means](machine-learning/clustering/k-means.md) * [DBSCAN](machine-learning/clustering/dbscan.md) * Metric * [Accuracy](machine-learning/metric/accuracy.md) * [Confusion Matrix](machine-learning/metric/confusion-matrix.md) * [Classification Report](machine-learning/metric/classification-report.md) * Workflow * [Pipeline](machine-learning/workflow/pipeline) * Neural Network * [Multilayer Perceptron Classifier](machine-learning/neural-network/multilayer-perceptron-classifier.md) * Cross Validation * [Random Split](machine-learning/cross-validation/random-split.md) * [Stratified Random Split](machine-learning/cross-validation/stratified-random-split.md) * Feature Selection * [Variance Threshold](machine-learning/feature-selection/variance-threshold.md) * [SelectKBest](machine-learning/feature-selection/selectkbest.md) * Preprocessing * [Normalization](machine-learning/preprocessing/normalization.md) * [Imputation missing values](machine-learning/preprocessing/imputation-missing-values.md) * Feature Extraction * [Token Count Vectorizer](machine-learning/feature-extraction/token-count-vectorizer.md) * [Tf-idf Transformer](machine-learning/feature-extraction/tf-idf-transformer.md) * Datasets * [Array](machine-learning/datasets/array-dataset.md) * [CSV](machine-learning/datasets/csv-dataset.md) * [Files](machine-learning/datasets/files-dataset.md) * [SVM](machine-learning/datasets/svm-dataset.md) * [MNIST](machine-learning/datasets/mnist-dataset.md) * Ready to use: * [Iris](machine-learning/datasets/demo/iris.md) * [Wine](machine-learning/datasets/demo/wine.md) * [Glass](machine-learning/datasets/demo/glass.md) * Models management * [Persistency](machine-learning/model-manager/persistency.md) * Math * [Distance](math/distance.md) * [Matrix](math/matrix.md) * [Set](math/set.md) * [Statistic](math/statistic.md) ## Contribute - Guide: [CONTRIBUTING.md](https://github.com/php-ai/php-ml/blob/master/CONTRIBUTING.md) - Issue Tracker: [github.com/php-ai/php-ml/issues](https://github.com/php-ai/php-ml/issues) - Source Code: [github.com/php-ai/php-ml](https://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)