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# PHP-ML - Machine Learning library for PHP
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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 ](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 >= 7.1.
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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, $labels);
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$classifier->predict([3, 2]);
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// return 'b'
```
## Documentation
To find out how to use PHP-ML follow [Documentation ](http://php-ml.readthedocs.org/ ).
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## Installation
Currently this library is in the process of developing, but You can install it with Composer:
```
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 Lerning
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* [Apriori ](machine-learning/association/apriori.md )
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* Classification
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* [SVC ](machine-learning/classification/svc.md )
* [k-Nearest Neighbors ](machine-learning/classification/k-nearest-neighbors.md )
* [Naive Bayes ](machine-learning/classification/naive-bayes.md )
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* Regression
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* [Least Squares ](machine-learning/regression/least-squares.md )
* [SVR ](machine-learning/regression/svr.md )
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* Clustering
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* [k-Means ](machine-learning/clustering/k-means.md )
* [DBSCAN ](machine-learning/clustering/dbscan.md )
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* Metric
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* [Accuracy ](machine-learning/metric/accuracy.md )
* [Confusion Matrix ](machine-learning/metric/confusion-matrix.md )
* [Classification Report ](machine-learning/metric/classification-report.md )
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* Workflow
* [Pipeline ](machine-learning/workflow/pipeline )
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* Neural Network
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* [Multilayer Perceptron Classifier ](machine-learning/neural-network/multilayer-perceptron-classifier.md )
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* Cross Validation
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* [Random Split ](machine-learning/cross-validation/random-split.md )
* [Stratified Random Split ](machine-learning/cross-validation/stratified-random-split.md )
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* Feature Selection
* [Variance Threshold ](machine-learning/feature-selection/variance-threshold.md )
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* [SelectKBest ](machine-learning/feature-selection/selectkbest.md )
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* Preprocessing
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* [Normalization ](machine-learning/preprocessing/normalization.md )
* [Imputation missing values ](machine-learning/preprocessing/imputation-missing-values.md )
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* Feature Extraction
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* [Token Count Vectorizer ](machine-learning/feature-extraction/token-count-vectorizer.md )
* [Tf-idf Transformer ](machine-learning/feature-extraction/tf-idf-transformer.md )
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* Datasets
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* [Array ](machine-learning/datasets/array-dataset.md )
* [CSV ](machine-learning/datasets/csv-dataset.md )
* [Files ](machine-learning/datasets/files-dataset.md )
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* [SVM ](machine-learning/datasets/svm-dataset.md )
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* Ready to use:
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* [Iris ](machine-learning/datasets/demo/iris.md )
* [Wine ](machine-learning/datasets/demo/wine.md )
* [Glass ](machine-learning/datasets/demo/glass.md )
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* Models management
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* [Persistency ](machine-learning/model-manager/persistency.md )
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* Math
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* [Distance ](math/distance.md )
* [Matrix ](math/matrix.md )
* [Set ](math/set.md )
* [Statistic ](math/statistic.md )
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## Contribute
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- 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 )
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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)