AWhat changed
Warmstarts structured Bayesian configuration search using related-dataset meta-features and constructs an ensemble from previously evaluated models in a scikit-learn pipeline search space.
Scientific scope
Warmstarts structured Bayesian configuration search using related-dataset meta-features and constructs an ensemble from previously evaluated models in a scikit-learn pipeline search space. CASH optimization, SMAC, meta-learning and greedy ensemble selection have inherited precedents; this is their system-level integration/extension, not invention of each ingredient. Fixed pipeline choices, datasets and resource budgets bound the evidence.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. CASH optimization, SMAC, meta-learning and greedy ensemble selection have inherited precedents; this is their system-level integration/extension, not invention of each ingredient. Fixed pipeline choices, datasets and resource budgets bound the evidence.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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