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Võrgu-juhuslik mets

Võrgu-juhuslik mets (ORF) laiendab klassikalist juhuslikku metsa voogedastuse seadetele, uuendades iga puud järk-järgult uute vaatluste saabumisel, ilma et salvestataks või taasesitataks kogu treeningkomplekti. Algoritmid, nagu adaptiivsed juhuslikud metsad (ARF), lisavad triivi tuvastamise, nii et ansambel kohandub, kui andmete jaotus aja jooksul muutub.

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Allikad

  1. Saffari, A., Leistner, C., Santner, J., Godec, M., & Bischof, H. (2009). On-line random forests. In Proceedings of the 3rd IEEE International Workshop on On-Line Learning for Computer Vision (OLCV 2009), pp. 1–8. IEEE. link
  2. Gomes, H. M., Bifet, A., Read, J., Barddal, J. P., Enembreck, F., Pfharinger, B., Holmes, G., & Abdessalem, T. (2017). Adaptive random forests for evolving data stream classification. Machine Learning, 106(9), 1469–1495. DOI: 10.1007/s10994-017-5642-8

Kuidas sellele lehele viidata

ScholarGate. (2026, June 3). Online Random Forest (Incremental Ensemble of Decision Trees). ScholarGate. https://scholargate.app/et/machine-learning/online-random-forest

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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.

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Sellele viitavad

ScholarGateOnline Random Forest (Online Random Forest (Incremental Ensemble of Decision Trees)). Loetud 2026-06-15 aadressilt https://scholargate.app/et/machine-learning/online-random-forest · Andmestik: https://doi.org/10.5281/zenodo.20539026