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Package php-ml
Short Description PHP-ML - Machine Learning library for PHP
License MIT
Homepage https://gitlab.com/php-ai/php-ml
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Informations about the package php-ml
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 >= 8.0. Use in any version >= 7.2 under your own responsibility.
Simple example of classification:
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:
Docker support
Current docker image php:8.2-fpm-alpine
See Docker section in CONTRIBUTING.md
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
- 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
- Clustering
- Metric
- Accuracy
- Confusion Matrix
- Classification Report
- Regression
- Workflow
- Pipeline
- FeatureUnion
- Neural Network
- Cross Validation
- Feature Selection
- Preprocessing
- Normalization
- Imputation missing values
- LabelEncoder
- LambdaTransformer
- NumberConverter
- ColumnFilter
- OneHotEncoder
- Feature Extraction
- Token Count Vectorizer
- NGramTokenizer
- WhitespaceTokenizer
- WordTokenizer
- Tf-idf Transformer
- Token Count Vectorizer
- Dimensionality Reduction
- PCA (Principal Component Analysis)
- Kernel PCA
- LDA (Linear Discriminant Analysis)
- Datasets
- Models management
- Math
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.
Authors & Contributors
- Arkadiusz Kondas (@ArkadiuszKondas)
- Rafael Espinosa (@rernesto)
