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# PHP-ML - Machine Learning library for PHP
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[![Minimum PHP Version ](https://img.shields.io/badge/php-%3E%3D%207.1-8892BF.svg )](https://php.net/)
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[![Latest Stable Version ](https://img.shields.io/packagist/v/php-ai/php-ml.svg )](https://packagist.org/packages/php-ai/php-ml)
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[![Documentation Status ](https://readthedocs.org/projects/php-ml/badge/?version=master )](http://php-ml.readthedocs.org/)
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< a href = "http://www.yegor256.com/2016/10/23/award-2017.html" >
< img src = "http://www.yegor256.com/images/award/2017/winner-itcraftsmanpl.png"
style="width:203px;height:45px;"/>< / a >
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![PHP-ML - Machine Learning library for PHP ](docs/assets/php-ml-logo.png )
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Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
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PHP-ML requires PHP >= 7.0.
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Simple example of classification:
```php
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require_once __DIR__ . '/vendor/autoload.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]];
$labels = ['a', 'a', 'a', 'b', 'b', 'b'];
$classifier = new KNearestNeighbors();
$classifier->train($samples, $labels);
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echo $classifier->predict([3, 2]);
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// return 'b'
```
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## Documentation
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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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Currently this library is in the process of being developed, but You can install it with Composer:
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```
composer require php-ai/php-ml
```
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## Examples
Example scripts are available in a separate repository [php-ai/php-ml-examples ](https://github.com/php-ai/php-ml-examples ).
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## Features
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* Association rule learning
* [Apriori ](http://php-ml.readthedocs.io/en/latest/machine-learning/association/apriori/ )
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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/ )
* [Naive Bayes ](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/naive-bayes/ )
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* Decision Tree (CART)
* Ensemble Algorithms
* Bagging (Bootstrap Aggregating)
* Random Forest
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* AdaBoost
* Linear
* Adaline
* Decision Stump
* Perceptron
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* LogisticRegression
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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/ )
* [DBSCAN ](http://php-ml.readthedocs.io/en/latest/machine-learning/clustering/dbscan/ )
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* Fuzzy C-Means
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* Metric
* [Accuracy ](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/accuracy/ )
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* [Confusion Matrix ](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/confusion-matrix/ )
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* [Classification Report ](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/classification-report/ )
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* Workflow
* [Pipeline ](http://php-ml.readthedocs.io/en/latest/machine-learning/workflow/pipeline )
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* Neural Network
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* [Multilayer Perceptron Classifier ](http://php-ml.readthedocs.io/en/latest/machine-learning/neural-network/multilayer-perceptron-classifier/ )
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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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* [Stratified Random Split ](http://php-ml.readthedocs.io/en/latest/machine-learning/cross-validation/stratified-random-split/ )
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* Preprocessing
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* [Normalization ](http://php-ml.readthedocs.io/en/latest/machine-learning/preprocessing/normalization/ )
* [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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* [Tf-idf Transformer ](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/tf-idf-transformer/ )
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* Dimensionality Reduction
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* PCA (Principal Component Analysis)
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* Kernel PCA
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* LDA (Linear Discriminant Analysis)
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* Datasets
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* [Array ](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/array-dataset/ )
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* [CSV ](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/csv-dataset/ )
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* [Files ](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/files-dataset/ )
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* Ready to use:
* [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/ )
* [Glass ](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/demo/glass/ )
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* Models management
* [Persistency ](http://php-ml.readthedocs.io/en/latest/machine-learning/model-manager/persistency/ )
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* Math
* [Distance ](http://php-ml.readthedocs.io/en/latest/math/distance/ )
* [Matrix ](http://php-ml.readthedocs.io/en/latest/math/matrix/ )
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* [Set ](http://php-ml.readthedocs.io/en/latest/math/set/ )
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* [Statistic ](http://php-ml.readthedocs.io/en/latest/math/statistic/ )
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* Linear Algebra
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## Contribute
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- [Issue Tracker: github.com/php-ai/php-ml ](https://github.com/php-ai/php-ml/issues )
- [Source Code: github.com/php-ai/php-ml ](https://github.com/php-ai/php-ml )
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You can find more about contributing in [CONTRIBUTING.md ](CONTRIBUTING.md ).
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## License
PHP-ML is released under the MIT Licence. See the bundled LICENSE file for details.
## Author
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Arkadiusz Kondas (@ArkadiuszKondas)