t-Distributed Stochastic Neighbor Embedding library with Barnes-Hut optimization.
Python implementation of Barnes-Hut-SNE with O(n log n) complexity for high-dimensional data visualization. Cython-optimized with Docker and Conda support.
- Barnes-Hut-SNE fast implementation
- O(n log n) complexity
- 2D/3D projection support
- Cython-optimized core
- Cross-platform (Linux, macOS, Windows)
- Example usage with Iris and MNIST datasets
| Layer | Technology |
|---|---|
| Language | Python 3.5+ |
| Core | Cython wrapper |
| Dependencies | NumPy >= 1.7.1, SciPy >= 0.12.0 |
| Environments | Docker, Conda |
pip install .
# Or with conda
conda install -c conda-forge tsneBSD-3-Clause