Density-Ratio Rescoring for Imbalanced Classification Using Raking Duals and Classifier Scores

arXiv:2609.23926 · stat.ML, cs.LG · Submitted 2026-09-20 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-20

Updated: 2026-09-22

Comments: 38 pages, 12 figures; includes all appendices

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 34× in this paper · explained in 2 episodes
• AUC — 32× in this paper · explained in 2 episodes
• Accuracy — 19× in this paper · explained in 1 episode
• Calibration — 16× in this paper · explained in 7 episodes
• Density-Ratio Rescoring — 6× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Regularization — 4× in this paper · explained in 3 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Covariate Shift — 1× in this paper · explained in 2 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Tabular Imbalanced Learning: A Survey, Benchmark, and Practical Guide

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