Funder
National Natural Science Foundation of China
Chunhui Project Foundation of the Education Department of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Reference69 articles.
1. Ke G, Meng Q, Finley T, Wang T, Chen W, Ma W, Ye Q, Liu TY (2017) Lightgbm: a highly efficient gradient boosting decision tree. Adv Neural Inf Process Syst 30:3146–3154
2. Chen T, Guestrin C (2016) XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA, pp 785-794. https://doi.org/10.1145/2939672.2939785
3. Dorogush AV, Ershov V, Gulin A (2018) CatBoost: gradient boosting with categorical features support. http://arxiv.org/abs/1810.11363
4. Tyralis H, Papacharalampous G (2021) Boosting algorithms in energy research: a systematic review. Neural Comput Appl 33(21):14101–14117. https://doi.org/10.1007/s00521-021-05995-8
5. Wang J, Jiang X, Meng Q, Saada M, Cai H (2022) Walking motion real-time detection method based on walking stick, IoT, COPOD and improved LightGBM. Appl Intell 45:1–19. https://doi.org/10.1007/s10489-022-03264-2
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