This project is a research-oriented tool for studying and experimenting with machine learning classifiers. The core is implemented in C++, exposed as an API that can be easily integrated with other languages such as Python, Go, Zig, and more.
- Provide a simple way to test machine learning algorithms in both C++ and Python.
- Start with implementations of classifiers and ensembles, then expand towards data stream mining.
- Build a modular API that allows integration with different programming languages.
- Follow an approach inspired by the MOA (Massive Online Analysis) project, but with a C++ core for efficiency and extensibility.
The main motivation of this project is to create a research tool that:
- Facilitates experimentation with machine learning algorithms.
- Bridges the gap between high-performance C++ implementations and the flexibility of Python scripting.
- Serves as a foundation to learn, compare, and extend algorithms for both static and streaming data.
- Pedro Bianchini de Quadros (project creator)
- [Add your name here if you contribute!]
This project welcomes contributions from everyone! Feel free to fork, submit issues, or create pull requests to help improve the project.
This project uses the GNU General Public License v3.0.