Research paper and software
Least-Squares Shapley Performance Attribution
An efficient method and open-source implementation for attributing the out-of-sample performance of a least-squares regression model to its input features using Shapley values.
Current state
The research was published in Statistics and Computing in 2024. The public LS-SPA package implements the method, includes a worked notebook and tests, and reached version 2.0.0 in January 2026. A separate repository preserves the paper’s benchmark implementation and experiments.
Details
- Phase
- Published paper · software v2.0.0
- Domain
- Statistics · interpretable machine learning
- My role
- Coauthor and developer
- With
- Nikhil Devanathan, Stephen Boyd
Artifacts
- Paper journal article
- Software repository repository
- Benchmark repository repository