Accelerate tree ensemble learning based on adaptive sampling

• Published in: Journal of computational methods in sciences and engineering Vol. 20; no. 2; pp. 509 - 519
• Main Authors: Zhou, Yu, Li, Hui, Chen, Mei, Dai, Zhenyu, Zhu, Ming
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2020; Sage Publications Ltd
• Subjects: Adaptive sampling; Data analysis; Decision trees; Ensemble learning; Machine learning; Sampling methods; adaptive sampling; scalable learning; mas-sart’s inequality; Gradient boosting decision tree

Gradient Boosting Decision Tree (GBDT) has been used extensively in machine learning applications due to its superiority in efficiency, accuracy and interpretability. Although there are already excellent and popular open source implementations such as XGBoost and LightGBM, etc., however, large data...