方法证据记录
Stacking
Stacking, or stacked generalization, is an ensemble method introduced by David Wolpert in 1992 that combines the outputs of several different base models (Level-0) through a separate meta-model (Level-1). Unlike bagging and boosting, it deliberately uses heterogeneous model types, and it is the standard final-stage strategy in Kaggle competitions.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Stacked Generalization (Stacking Ensemble with a Meta-Learner)
分类方法记录 · ml-model / machine-learning
- Wolpert, D.H. (1992). Stacked Generalization. Neural Networks, 5(2), 241–259. · DOI 10.1016/S0893-6080(05)80023-1
- van der Laan, M.J., Polley, E.C. & Hubbard, A.E. (2007). Super Learner. Statistical Applications in Genetics and Molecular Biology, 6(1), Article 25. · DOI 10.2202/1544-6115.1309
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