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Stacking

Algorithms AIMech:Stacking DRAFT

Aliases: Stacked generalization

Ensemble learning that trains a final estimator on base-estimator predictions.

Identity Notes & Concept Scope EnsembleLearning does not require a learned final estimator on base-estimator predictions.

Claims & Grounded Evidence

1 Claim

Mechanism #mechanism

A final estimator learns from predictions of base estimators; held-out predictions can separate its training from base-estimator fitting.

supports Source: scikit-learn User Guide: ensemble · Locator: User Guide, section #stacked-generalization

This record supports method identity and the stated mechanism only; no universal performance or biological efficacy claim is curated.
Proposed placement is an inference from the existing AIO hierarchy; maintainers must resolve task, algorithm and model scope before acceptance.

Mapped AIO Classes

AIO Target Class	Mapping Relation	Mapping Rationale
`AIO:EnsembleLearning` Ensemble Learning	related_match	EnsembleLearning does not require a learned final estimator on base-estimator predictions. Mapping is local curation, not an upstream subclass assertion.

1 Source

Source ID	Publication / Document	Type / Access	Reference & Checksum
`method-source`	scikit-learn User Guide: ensemble scikit-learn developers	official documentation documentation	sha256:8014d31b6fc9…

Curator: Codex

Method: ai_assisted

Model: GPT-6

Created: 2026-10-11T03:01:34Z

Updated: 2026-10-11T03:01:34Z

Source File: data/curated/Stacking.yaml