mirror of
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131 lines
6.2 KiB
Markdown
131 lines
6.2 KiB
Markdown
# PHP-ML - Machine Learning library for PHP
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[](https://php.net/)
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[](https://packagist.org/packages/php-ai/php-ml)
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[](https://scrutinizer-ci.com/g/php-ai/php-ml/build-status/master)
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[](http://php-ml.readthedocs.org/)
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[](https://packagist.org/packages/php-ai/php-ml)
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[](https://packagist.org/packages/php-ai/php-ml)
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[](https://coveralls.io/github/php-ai/php-ml?branch=coveralls)
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[](https://scrutinizer-ci.com/g/php-ai/php-ml/?branch=master)
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<a href="http://www.yegor256.com/2016/10/23/award-2017.html">
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<img src="http://www.yegor256.com/images/award/2017/winner-itcraftsmanpl.png"
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style="width:203px;height:45px;"/></a>
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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:
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```php
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require_once __DIR__ . '/vendor/autoload.php';
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use Phpml\Classification\KNearestNeighbors;
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$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
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$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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echo $classifier->predict([3, 2]);
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// return 'b'
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```
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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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```
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composer require php-ai/php-ml
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```
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## Examples
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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
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* [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/)
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* [Naive Bayes](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/naive-bayes/)
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* Decision Tree (CART)
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* Ensemble Algorithms
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* Bagging (Bootstrap Aggregating)
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* Random Forest
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* AdaBoost
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* Linear
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* Adaline
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* Decision Stump
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* 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/)
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* [DBSCAN](http://php-ml.readthedocs.io/en/latest/machine-learning/clustering/dbscan/)
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* Fuzzy C-Means
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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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* [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
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* [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/)
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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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* [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:
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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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* Models management
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* [Persistency](http://php-ml.readthedocs.io/en/latest/machine-learning/model-manager/persistency/)
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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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* [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)
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- [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
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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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Arkadiusz Kondas (@ArkadiuszKondas)
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