php-ml/README.md
2019-05-15 08:00:46 +02:00

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# PHP-ML - Machine Learning library for PHP
[![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.2-8892BF.svg)](https://php.net/)
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[![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=master)](http://php-ml.readthedocs.org/)
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<p align="center">
<img src="https://github.com/php-ai/php-ml/raw/master/docs/assets/php-ml-logo.png" />
</p>
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 >= 7.2.
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);
echo $classifier->predict([3, 2]);
// return 'b'
```
## Awards
<a href="http://www.yegor256.com/2016/10/23/award-2017.html">
<img src="http://www.yegor256.com/images/award/2017/winner-itcraftsmanpl.png" width="400"/></a>
## 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 being developed, 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).
## Datasets
Public datasets are available in a separate repository [php-ai/php-ml-datasets](https://github.com/php-ai/php-ml-datasets).
## Features
* Association rule learning
* [Apriori](http://php-ml.readthedocs.io/en/latest/machine-learning/association/apriori/)
* Classification
* [SVC](http://php-ml.readthedocs.io/en/latest/machine-learning/classification/svc/)
* [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/)
* Decision Tree (CART)
* Ensemble Algorithms
* Bagging (Bootstrap Aggregating)
* Random Forest
* AdaBoost
* Linear
* Adaline
* Decision Stump
* Perceptron
* LogisticRegression
* Regression
* [Least Squares](http://php-ml.readthedocs.io/en/latest/machine-learning/regression/least-squares/)
* [SVR](http://php-ml.readthedocs.io/en/latest/machine-learning/regression/svr/)
* DecisionTreeRegressor
* Clustering
* [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/)
* Fuzzy C-Means
* Metric
* [Accuracy](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/accuracy/)
* [Confusion Matrix](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/confusion-matrix/)
* [Classification Report](http://php-ml.readthedocs.io/en/latest/machine-learning/metric/classification-report/)
* Regression
* Workflow
* [Pipeline](http://php-ml.readthedocs.io/en/latest/machine-learning/workflow/pipeline)
* FeatureUnion
* Neural Network
* [Multilayer Perceptron Classifier](http://php-ml.readthedocs.io/en/latest/machine-learning/neural-network/multilayer-perceptron-classifier/)
* Cross Validation
* [Random Split](http://php-ml.readthedocs.io/en/latest/machine-learning/cross-validation/random-split/)
* [Stratified Random Split](http://php-ml.readthedocs.io/en/latest/machine-learning/cross-validation/stratified-random-split/)
* Feature Selection
* [Variance Threshold](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-selection/variance-threshold/)
* [SelectKBest](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-selection/selectkbest/)
* Preprocessing
* [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/)
* LabelEncoder
* LambdaTransformer
* NumberConverter
* ColumnFilter
* OneHotEncoder
* Feature Extraction
* [Token Count Vectorizer](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/token-count-vectorizer/)
* NGramTokenizer
* WhitespaceTokenizer
* WordTokenizer
* [Tf-idf Transformer](http://php-ml.readthedocs.io/en/latest/machine-learning/feature-extraction/tf-idf-transformer/)
* Dimensionality Reduction
* PCA (Principal Component Analysis)
* Kernel PCA
* LDA (Linear Discriminant Analysis)
* Datasets
* [Array](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/array-dataset/)
* [CSV](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/csv-dataset/)
* [Files](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/files-dataset/)
* [SVM](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/svm-dataset/)
* [MNIST](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/mnist-dataset.md)
* Ready to use:
* [Iris](http://php-ml.readthedocs.io/en/latest/machine-learning/datasets/demo/iris/)
* [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/)
* Models management
* [Persistency](http://php-ml.readthedocs.io/en/latest/machine-learning/model-manager/persistency/)
* Math
* [Distance](http://php-ml.readthedocs.io/en/latest/math/distance/)
* [Matrix](http://php-ml.readthedocs.io/en/latest/math/matrix/)
* [Set](http://php-ml.readthedocs.io/en/latest/math/set/)
* [Statistic](http://php-ml.readthedocs.io/en/latest/math/statistic/)
* Linear Algebra
## Contribute
- [Guide: CONTRIBUTING.md](https://github.com/php-ai/php-ml/blob/master/CONTRIBUTING.md)
- [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)
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)