ElasticNet
Cross-source consensus on ElasticNet from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Benefits
Comparisons
Evidence quality
Highlighted claims
- ElasticNetCV provides the anchored alpha that enables StackFeat-RL's computational improvement. — StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery
- Using a single tuned regularisation value avoids nested cross-validation at every StackFeat iteration. — StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery
- ElasticNetCV is treated as a strong embedded baseline but can depend on partitioning and retain large correlated feature groups. — StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery
- On COVID-19 miRNA data, ElasticNet had the highest mean AUC but used more than twice as many features as StackFeat-RL. — StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery