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# PHP-ML - Machine Learning library for PHP
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2016-02-08 22:07:16 +00:00
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2016-04-08 21:22:55 +00:00
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[![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)
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2016-04-08 22:50:08 +00:00
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[![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=develop)](http://php-ml.readthedocs.org/en/develop/?badge=develop)
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2016-04-08 21:22:55 +00:00
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[![Total Downloads](https://poser.pugx.org/php-ai/php-ml/downloads.svg)](https://packagist.org/packages/php-ai/php-ml)
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[![License](https://poser.pugx.org/php-ai/php-ml/license.svg)](https://packagist.org/packages/php-ai/php-ml)
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[![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)
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2016-02-08 22:07:16 +00:00
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2016-05-02 10:07:53 +00:00
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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 ...
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Simple example of classification:
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```php
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use Phpml\Classification\KNearestNeighbors;
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$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
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$labels = ['a', 'a', 'a', 'b', 'b', 'b'];
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$classifier = new KNearestNeighbors();
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$classifier->train($samples, $labels);
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$classifier->predict([3, 2]);
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// return 'b'
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```
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2016-04-08 21:22:55 +00:00
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## Documentation
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2016-02-08 22:20:08 +00:00
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2016-04-08 22:53:18 +00:00
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To find out how to use PHP-ML follow [Documentation](http://php-ml.readthedocs.org/).
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## Installation
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2016-04-08 21:22:55 +00:00
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Currently this library is in the process of developing, but You can install it with Composer:
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```
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composer require php-ai/php-ml
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```
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## Features
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* Classification
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* [SVC](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/svc/)
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* [k-Nearest Neighbors](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/k-nearest-neighbors/)
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* [Naive Bayes](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/naive-bayes/)
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* Regression
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* [Least Squares](http://php-ml.readthedocs.io/en/latest/machine-learning/regression/least-squares/)
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* [SVR](http://php-ml.readthedocs.io/en/latest/machine-learning/regression/svr/)
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* Clustering
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* [k-Means](http://php-ml.readthedocs.io/en/latest/machine-learning/clustering/k-means/)
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* [DBSCAN](http://php-ml.readthedocs.io/en/latest/machine-learning/clustering/dbscan/)
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* Metric
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* [Accuracy](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/accuracy/)
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* Cross Validation
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* [Random Split](http://php-ml.readthedocs.io/en/latest/machine-learning/cross-validation/random-split/)
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* Preprocessing
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* [Normalization](http://php-ml.readthedocs.io/en/latest/machine-learning/preprocessing/normalization/)
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* [Imputation missing values](http://php-ml.readthedocs.io/en/latest/machine-learning/preprocessing/imputation-missing-values/)
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* Feature Extraction
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* [Token Count Vectorizer](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/token-count-vectorizer/)
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* Datasets
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* [CSV](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/csv-dataset/)
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* Ready to use:
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* [Iris](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/demo/iris/)
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* [Wine](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/demo/wine/)
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* [Glass](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/demo/glass/)
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* Math
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* [Distance](http://php-ml.readthedocs.io/en/latest/math/distance/)
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* [Matrix](http://php-ml.readthedocs.io/en/latest/math/matrix/)
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* [Statistic](http://php-ml.readthedocs.io/en/latest/math/statistic/)
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2016-02-08 22:07:16 +00:00
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2016-05-02 10:07:53 +00:00
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## Contribute
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- Issue Tracker: github.com/php-ai/php-ml/issues
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- Source Code: github.com/php-ai/php-ml
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2016-05-02 10:07:53 +00:00
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After installation, you can launch the test suite in project root directory (you will need to install dev requirements with Composer)
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```
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bin/phpunit
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```
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## License
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PHP-ML is released under the MIT Licence. See the bundled LICENSE file for details.
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## Author
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2016-05-02 10:07:53 +00:00
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Arkadiusz Kondas (@ArkadiuszKondas)
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