All notable changes to the OpenModels project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Initial release of OpenModels library
- Core functionality for serializing and deserializing machine learning models
- Support for scikit-learn models:
- Classification: LogisticRegression, RandomForestClassifier, SVC, BernoulliNB, GaussianNB, MultinomialNB, ComplementNB, Perceptron
- Regression: LinearRegression, Lasso, Ridge, RandomForestRegressor, SVR
- Clustering: KMeans
- Dimensionality Reduction: PCA
- Other: PLSRegression
- JSON serialization format
- Pickle serialization format
- Extensible architecture for adding new model types and serialization formats
- Basic test suite for supported models
- Documentation including README, LICENSE, and CONTRIBUTING guidelines
- N/A (First release)
- N/A (First release)
- N/A (First release)
- N/A (First release)
- Implemented safe alternatives to pickle serialization
- Support for TensorFlow models
- YAML serialization format
- Enhanced documentation with more examples and use cases
- Improved test coverage
- Support for more scikit-learn models including ensemble methods and neural networks