Showing 2026Show all
2 papers · 1 filter
cs.LG2026
SR4-Fit: An Interpretable and Informative Classification Algorithm Applied to Prediction of U.S. House of Representatives Elections
Shyam Sundar Murali Krishnan, Dean Frederick Hougen
The growth of machine learning demands interpretable models for critical applications, yet most high-performing models are ``black-box'' systems that obscure input-output relations…
cs.NE2026
Evolving Multi-Channel Confidence-Aware Activation Functions for Missing Data with Channel Propagation
Naeem Shahabi Sani, Ferial Najiantabriz, Shayan Shafaei +1
Learning in the presence of missing data can result in biased predictions and poor generalizability, among other difficulties, which data imputation methods only partially address.…