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Striders is a surrogate-based explainable AI (XAI) library for efficient feature attribution. It uses landmark-based kernel approximations to reduce the computational cost of generating additive feature contributions, providing a scalable alternative to SHAP for tabular models.

Installation

pip install striders

Performance Benchmarking

Dataset (Task) Samples / Features Metric TreeSHAP Striders Speed-up
CA Housing (Reg.) 20,640 / 8 Execution Time 22.1948s 0.3927s 56.5x 🚀
Fidelity ($R^2$) - 0.9081
Correlation - 0.9490
Credit Default (Clf.) 30,000 / 23 Execution Time 47.0008s 2.4718s 19.0x 🚀
Fidelity ($R^2$) - 0.9776
Correlation - 0.9429

Reproducibility: You can run directly in: Open In Colab

Acknowledgments & Citations

This is an unofficial implementation based on the principles described in:

@article{ko2025stride,
  title={STRIDE: Subset-Free Functional Decomposition for XAI in Tabular Settings},
  author={Ko, Chaeyun},
  journal={arXiv preprint arXiv:2509.09070},
  year={2025}
}

Metadata

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striders-0.1.1-cp38-abi3-win_amd64.whl CPython 3.8 abi3 Windows x86-64 Details for striders-0.1.1-cp38-abi3-win_amd64.whl
striders-0.1.1-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.8 abi3 Linux glibc 2.17+ x86-64 Details for striders-0.1.1-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
striders-0.1.1-cp38-abi3-macosx_11_0_arm64.whl CPython 3.8 abi3 macOS 11.0+ ARM64 Details for striders-0.1.1-cp38-abi3-macosx_11_0_arm64.whl

Total release size: 2.6 MB

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