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Bayesian LightGBM×LightGBM×
OdborStrojové učenieStrojové učenie
RodinaMachine learningMachine learning
Rok vzniku2017 (LightGBM); 2012 (Bayesian optimization)2017
TvorcaKe et al. (LightGBM); Snoek et al. (Bayesian optimization)Ke, G. et al. (Microsoft)
TypGradient boosting with Bayesian hyperparameter searchGradient boosting decision tree ensemble
Pôvodný zdrojKe, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., & Liu, T.-Y. (2017). LightGBM: A highly efficient gradient boosting decision tree. In Advances in Neural Information Processing Systems, 30, 3146–3154. link ↗Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q. & Liu, T.-Y. (2017). LightGBM: A Highly Efficient Gradient Boosting Decision Tree. Advances in Neural Information Processing Systems (NeurIPS) 30, 3146–3154. link ↗
Ďalšie názvyBayesian-tuned LightGBM, LightGBM + Bayesian optimization, BayesOpt LightGBM, LightGBM with BayesOptLightGBM, Light Gradient Boosting Machine, lgbm, leaf-wise gradient boosting
Príbuzné55
ZhrnutieBayesian LightGBM combines LightGBM — a highly efficient histogram-based gradient boosting framework — with Bayesian hyperparameter optimization. Instead of exhaustive grid search or random search, a probabilistic surrogate model guides the search for optimal hyperparameters, dramatically reducing the number of costly model evaluations needed to reach strong predictive performance.LightGBM is Microsoft's gradient boosting decision tree implementation, introduced by Ke and colleagues in 2017, that grows trees leaf-wise and bins features into histograms for speed. On large datasets it is much faster than XGBoost while retaining strong predictive accuracy.
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ScholarGatePorovnať metódy: Bayesian LightGBM · LightGBM. Získané 2026-06-18 z https://scholargate.app/sk/compare