Unverified50% confidenceOpinionExact time
MAS and Model-X knockoffs are complementary: when the covariate distribution is known or can be estimated accurately, knockoffs may be the more efficient choice; when the distribution is unknown or difficult to model, MAS exhibits a model-agnostic advantage.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedA new study proposes a complementary method called MAS (Model-Agnostic Selection with agent-X importance) for achieving FDR-controlled variable selection without assumptions on the covariate distribution.75% similarUnverified多Agent系统（MAS）在投研场景中通过不同Agent专注于不同维度的分析，比单一大模型直接输出结论具有更强的可解释性和鲁棒性71% similarUnverifiedMAS introduces a 'resplit-per-covariate' strategy, which decouples the dependencies among estimators by independently resampling for each covariate.68% similarUnverifiedModel-X knockoffs does not depend on the model form of the outcome variable Y, and only requires that the distribution of the covariates X is known.65% similarUnverifiedThe classical model competitors in the comparison experiment include algorithms such as SVM, XGBoost, and logistic regression.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1046181API
curl https://kongchang.com/api/v1/knowledge/claims/1046181MCP
get_claim(id=1046181)