ScholarGate
Assistent
Machine learningMachine learning

Bayesian Stacking Ensemble

Bayesian stacking ühendab mitme baasmudeli ennustusjaotused, leides mitte-negatiivsed kaalud, mis maksimeerivad segu jäetud-üks-välja (leave-one-out, LOO) log-ennustus skoori. Yao, Vehtari, Simpsoni ja Gelmani (2018) poolt formaliseeritud meetod annab ühe kalibreeritud ennustusjaotuse, mis on ristvalideerimise alusel tõestatult vähemalt sama hea kui ükski üksik koostisosa mudel.

Ava rakenduses MethodMindPeagiVideoPeagiDownload slides

Loe meetodi täielikku kirjeldust

Ainult liikmetele

Selle osa lugemiseks logi sisse tasuta kontoga.

Logi sisse

Method map

The neighbourhood of related methods — select a node to explore.

Allikad

  1. Yao, Y., Vehtari, A., Simpson, D., & Gelman, A. (2018). Using stacking to average Bayesian predictive distributions. Bayesian Analysis, 13(3), 917–1007. DOI: 10.1214/17-BA1091
  2. Wolpert, D. H. (1992). Stacked generalization. Neural Networks, 5(2), 241–259. DOI: 10.1016/S0893-6080(05)80023-1

Kuidas sellele lehele viidata

ScholarGate. (2026, June 3). Bayesian Stacking Ensemble (Bayesian Stacking of Predictive Distributions). ScholarGate. https://scholargate.app/et/machine-learning/bayesian-stacking-ensemble

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateBayesian Stacking Ensemble (Bayesian Stacking Ensemble (Bayesian Stacking of Predictive Distributions)). Loetud 2026-06-15 aadressilt https://scholargate.app/et/machine-learning/bayesian-stacking-ensemble · Andmestik: https://doi.org/10.5281/zenodo.20539026