Results 101 to 110 of about 66,452 (290)
, 2023 Shapley values attempt to explain ML models using flat additive factors disregarding any tree hierarchy, and fails to distinguish between two different trees. We have been using log odds for segmentation tree of logistic regression models. Log odds faithfully reflect tree hierarchy and therefore explain decision trees, forests, and GBM much better.
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
A study on the factors influencing the utilization of public health services by China's migrant population based on the Shapley value method. [PDF]
BMC Public Health, 2023 Suo Z, Shao L, Lang Y.
europepmc +1 more source
Implementation of the Ordinal Shapley Value for a three-agent economy [PDF]
We propose a simple mechanism that implements the Ordinal Shapley Value (Pérez-Castrillo and Wettstein [2005]) for economies with three or less agents.Ordinal Shapley Value, implementation, mechanism ...
David Pérez-Castrillo, David Wettstein
core
The paper explores different applications of the Shapley value for either inequality or poverty measures. We first investigate the problem of source decomposition of inequality measures, the so-called additive income sources inequality games, baed on the
Arthur Charpentier, Stéphane Mussard
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Artificial Intelligence for Bone: Theory, Methods, and Applications
Advanced Intelligent Discovery, EarlyView.Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
EdgeSHAPer: Bond-centric Shapley value-based explanation method for graph neural networks. [PDF]
iScience, 2022 Mastropietro A +4 more
europepmc +1 more source
A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
Advanced Intelligent Discovery, EarlyView.This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source
Differences in learning characteristics between support vector machine and random forest models for compound classification revealed by Shapley value analysis. [PDF]
Sci Rep, 2023 Siemers FM, Bajorath J.
europepmc +1 more source
New Axiomatizations and an Implementation of the Shapley Value [PDF]
Some new axiomatic characterizations and recursive formulas of the Shapley value are presented. In the results, dual games and the self-duality of the value implicitly play an important role.
Funaki, Y., Kongo, T., Tijs, S.H.
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