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Assessing model calibration with boosting trees

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arXiv:2606. 08084v1 Announce Type: cross Abstract: The main goal in regression modelling consists in approximating the conditional mean of a response given a set of features.

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Authors: Selim Gatti
Released: 2026-06-09 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Assessing model calibration with boosting trees overlaps with clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation", experiment "Test FR↔IT bystander-spill symmetry at multi-seed + 5 phrasings — pooled-rate vs per-phrasing asymmetry from #239 fact-check". Matching terms: rate, test, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2606.08084

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