all AI news
The Shapley Value of coalition of variables provides better explanations. (arXiv:2103.13342v3 [stat.ML] UPDATED)
April 7, 2022, 1:12 a.m. | Salim I. Amoukou, Nicolas J-B. Brunel, Tangi Salaün
cs.LG updates on arXiv.org arxiv.org
While Shapley Values (SV) are one of the gold standard for interpreting
machine learning models, we show that they are still poorly understood, in
particular in the presence of categorical variables or of variables of low
importance. For instance, we show that the popular practice that consists in
summing the SV of dummy variables is false as it provides wrong estimates of
all the SV in the model and implies spurious interpretations. Based on the
identification of null and active …
More from arxiv.org / cs.LG updates on arXiv.org
A Single-Loop Algorithm for Decentralized Bilevel Optimization
1 day, 5 hours ago |
arxiv.org
CLEANing Cygnus A deep and fast with R2D2
1 day, 5 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Alternant Data Engineering
@ Aspire Software | Angers, FR
Senior Software Engineer, Generative AI
@ Google | Dublin, Ireland