Initial Release
First public release of decision-boundary — a universal visualization library for N-dimensional machine learning decision boundaries. Works with scikit-learn, Keras, and PyTorch Lightning models, rendering interactive 2D/3D boundaries via Matplotlib or Plotly, in scripts, Jupyter, and Colab.
Install
Install the base package via pip:
pip install decision-boundary-plot
Optional Extras:
Depending on your framework and needs, you can install optional dependencies.
Note: Always use quotes around the package name when installing extras to prevent terminal errors.
# Dimensionality Reduction
pip install "decision-boundary-plot[umap]" # UMAP algorithm for complex data
# Framework Callbacks (Live Visualization)
pip install "decision-boundary-plot[keras]" # Keras model support
pip install "decision-boundary-plot[lightning]" # PyTorch Lightning support
pip install "decision-boundary-plot[sklearn-callbacks]" # scikit-learn live training (needs >=1.9.0)
# Export Utilities
pip install "decision-boundary-plot[export]" # Static 3D image export via kaleido
# Install Everything
pip install "decision-boundary-plot[all]" # Includes all the features above
Requirements
- Python 3.11+
- See
pyproject.tomlfor the full dependency list.
Links
- 📦 PyPI: https://pypi.org/project/decision-boundary-plot/
- 📖 README: https://github.com/P3Lin0r/decision-boundary#readme
Full Changelog: https://github.com/P3Lin0r/decision-boundary/commits/v0.1.0