Model Selection
Cross-source consensus on Model Selection from 1 sources and 4 claims.
1 sources · 4 claims
Risks & contraindications
Evidence quality
Highlighted claims
- The number of templates is selected using WAIC, held-out link prediction, and consensus stability. — A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis
- Held-out topology prediction evaluates posterior mean edge-presence probabilities by ROC AUC. — A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis
- Stability assessment aligns templates across independent runs to handle label switching. — A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis
- WAIC should not be used alone because it may mildly decrease as template count increases. — A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis