Semi-supervisert CatBoost
Semi-supervisert CatBoost anvender CatBoosts rammeverk for ordnet gradient-boosting på innstillinger der bare en brøkdel av treningsinstansene har etiketter, og utnytter umerkede data gjennom pseudo-etikettering eller konsistensbaserte strategier for å forbedre modellens nøyaktighet utover det merkede data alene ville tillate.
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Method map
The neighbourhood of related methods — select a node to explore.
Kilder
- Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V., & Gulin, A. (2018). CatBoost: unbiased boosting with categorical features. In Advances in Neural Information Processing Systems (NeurIPS), 31. link ↗
- Chapelle, O., Scholkopf, B., & Zien, A. (Eds.). (2006). Semi-Supervised Learning. MIT Press. ISBN: 978-0-262-03358-9
Slik siterer du denne siden
ScholarGate. (2026, June 3). Semi-supervised CatBoost (Gradient Boosting with Partially Labeled Data). ScholarGate. https://scholargate.app/no/machine-learning/semi-supervised-catboost
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.
- CatBoostMaskinlæring↔ compare
- Gradient BoostingMaskinlæring↔ compare
- Semi-supervised Gradient BoostingMaskinlæring↔ compare
- Semi-supervised Random ForestMaskinlæring↔ compare
- Semi-supervised XGBoostMaskinlæring↔ compare
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