arXiv (All)
open access
Exact and Certified Data Shapley for Weighted Nearest Neighbor Regression
Data Shapley can be computed exactly and efficiently for unweighted K-nearest-neighbor (KNN) models, the basis of the popular KNN-Shapley. For weighted KNN, however, efficient exact algorithms are known only for hard-label classification. In regression, the prediction is a weighted average whose nor
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Near-Exponential Convergence Rates for kNN Classification based on Boltzmann Margin#1356078
- Evaluating the Causal Faithfulness of SHAP as a Candidate Attribution Method for SAE Features#1343097
- HRNN: A Hybrid Graph Index for Approximate Reverse k-Nearest Neighbor Search on High-Dimensional Vectors#259606
- A Generalisation Signal Need Not Be a Model-Selection Signal#1144066
- Characterizing the Separability Gap in Prior-Data Fitted Networks#1325885
Record · ID 1199909
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive