PHP-ML - Machine Learning library for PHP

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 >= 7.1.

Simple example of classification:

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

Documentation

To find out how to use PHP-ML follow Documentation.

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.

Datasets

Public datasets are available in a separate repository php-ai/php-ml-datasets.

Features

• Association rule learning
  • Apriori
• Classification
  • SVC
  • k-Nearest Neighbors
  • Naive Bayes
  • Decision Tree (CART)
  • Ensemble Algorithms
    • Bagging (Bootstrap Aggregating)
    • Random Forest
    • AdaBoost
  • Linear
    • Adaline
    • Decision Stump
    • Perceptron
    • LogisticRegression
• Regression
  • Least Squares
  • SVR
• Clustering
  • k-Means
  • DBSCAN
  • Fuzzy C-Means
• Metric
  • Accuracy
  • Confusion Matrix
  • Classification Report
• Workflow
  • Pipeline
• Neural Network
  • Multilayer Perceptron Classifier
• Cross Validation
  • Random Split
  • Stratified Random Split
• Feature Selection
  • Variance Threshold
  • SelectKBest
• Preprocessing
  • Normalization
  • Imputation missing values
• Feature Extraction
  • Token Count Vectorizer
    • NGramTokenizer
    • WhitespaceTokenizer
    • WordTokenizer
  • Tf-idf Transformer
• Dimensionality Reduction
  • PCA (Principal Component Analysis)
  • Kernel PCA
  • LDA (Linear Discriminant Analysis)
• Datasets
  • Array
  • CSV
  • Files
  • SVM
  • MNIST
  • Ready to use:
    • Iris
    • Wine
    • Glass
• Models management
  • Persistency
• Math
  • Distance
  • Matrix
  • Set
  • Statistic
  • Linear Algebra

Contribute

• Guide: CONTRIBUTING.md
• Issue Tracker: github.com/php-ai/php-ml
• Source Code: github.com/php-ai/php-ml

You can find more about contributing in CONTRIBUTING.md.

License

PHP-ML is released under the MIT Licence. See the bundled LICENSE file for details.

Author

Arkadiusz Kondas (@ArkadiuszKondas)