مقایسهٔ روشها
روشهای انتخابی خود را کنار هم مرور کنید؛ ردیفهای متفاوت برجسته شدهاند.
| LightGBM نیمهنظارتشده (Semi-supervised LightGBM)× | لایتجیبیام (LightGBM)× | |
|---|---|---|
| حوزه | یادگیری ماشین | یادگیری ماشین |
| خانواده | Machine learning | Machine learning |
| سال پیدایش≠ | 2017–2019 | 2017 |
| پدیدآور≠ | Ke, G. et al. (LightGBM); semi-supervised extension via community practice and research | Ke, G. et al. (Microsoft) |
| نوع≠ | Semi-supervised gradient boosting ensemble | Gradient boosting decision tree ensemble |
| منبع بنیادین≠ | 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, 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 ↗ |
| نامهای دیگر | SSL-LightGBM, pseudo-label LightGBM, self-training LightGBM, semi-supervised GBDT | LightGBM, Light Gradient Boosting Machine, lgbm, leaf-wise gradient boosting |
| مرتبط≠ | 4 | 5 |
| خلاصه≠ | Semi-supervised LightGBM combines LightGBM's highly efficient gradient boosting framework with semi-supervised strategies — most commonly pseudo-labeling or self-training — to exploit large pools of unlabeled data alongside a smaller labeled set, improving predictive performance when obtaining labels is costly or time-consuming. | 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. |
| ScholarGateمجموعهداده ↗ |
|
|