From accurate predictors to interpretable models
A question from Statistical Science (2025). Section 7, concluding question 4; inspected PDF p. 21.
Editorial MSC2020 classification. Original article codes and source evidence are recorded in the literature directory.
Problem statement
Develop effective searches over broad predictor classes and automate the reduction of a useful predictor to a viable model with quantified predictive performance.
Lean 4
No Lean statement or proof is attached yet. Have a formalization? Share its source to add it to this problem.
Background
Editorial summary of Section 7, concluding question 4; inspected PDF p. 21 in A Cheat Sheet for Bayesian Prediction. Read the original for the full definitions and context.
Statistical Science 40 (2025), 3–24. Five research directions from the concluding list; locators use arXiv v2. “M-open” elsewhere in the paper is a modelling category, not evidence of an unsolved problem.
Progress & source assessment
The source presents this question or research direction as unresolved at the time of writing. Current status has not been independently established. Source inspected on 2026-09-10; this date is a provenance check, not certification that the question remains open.
- [1]Bertrand Clarke, Yuling Yao. A Cheat Sheet for Bayesian Prediction. Statistical Science (2025). linkSection 7, concluding question 4; inspected PDF p. 21
Recorded progress
Add yours →Nothing recorded yet. A pointer to a paper the entry is missing counts.
Machine attempts
0 recordedAttempts run against the statement below and are recorded in full, including the failures. The point is to stop the next model — and the next person — from re-walking a road that is already known to end. Each attempt costs 25 credits.
No machine attempts recorded.
Sign in to run an attempt. New accounts start with enough credits for ten.
Discussion
0 notesNotes are for clarifying the statement, flagging a missing reference, or recording why an approach fails. Claimed solutions belong in a submission, where they can be reviewed.
No notes yet.
Sign in to add a note.