README

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This is a port of PHP-ML library (https://gitlab.com/php-ai/php-ml) to make it work on PHP 8. The original library was created by Arkadiusz Kondas (@ArkadiuszKondas).

This port has been created by Michal Hynčica

PORT NOTES

Done during port

• The error when Phpml\Classification\Ensemble\Bagging was creating the Phpml\Classification\DecisionTree instance has been fixed
• Fixed expected result in SetTest::testToArray() to reflect introduction of stable sorting in php 8.
• The required version of phpbench/phpbench in composer.json has been changed to ^1.0.0 so it can be installed on php 8. The phpbench isn't working currently. Its config need some more work.
• The required version of symplify/easy-coding-standards has been increased to ^9.4. The config has been converted for newer version.

Failing test

The test DecisionStumpTest::testPredictSingleSample is currently failing. This is caused by introduction of stable sorting in php 8. The problem is in Phpml\Classification\Classifier\OneVsRest::predictSample method. For non-binary decision stump this method gets probability for all classifiers. It uses arsort() to order label by its probability then return the first label as most probable result.

In test case the probabilities looks like this:

[
   '0' => 0.0,
   '1' => 1.0,
   '2' => 1.0,
];

Before introduction of stable sorting the order of elements with same value wasn't well defined and by some luck the reverse sorted array looked like this:

[
   '2' => 1.0,
   '1' => 1.0,
   '0' => 0.0,
];

But, with stable sorting introduced the reverse sorted array looks like this:

[
   '1' => 1.0,
   '2' => 1.0,
   '0' => 0.0,
];

This is the cause the result is different from what is expected in test.

Installation

Currently this library is in the process of being developed, but You can install it with Composer:

composer require hyncica/php8-ml

The rest is content of original README.md file.

PHP-ML requires PHP >= 7.2.

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.

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
  • Regression
• Workflow
  • Pipeline
  • FeatureUnion
• Neural Network
  • Multilayer Perceptron Classifier
• Cross Validation
  • Random Split
  • Stratified Random Split
• Feature Selection
  • Variance Threshold
  • SelectKBest
• Preprocessing
  • Normalization
  • Imputation missing values
  • LabelEncoder
  • LambdaTransformer
  • NumberConverter
  • ColumnFilter
  • OneHotEncoder
• 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)