Stacking Based LightGBM-CatBoost-RandomForest Algorithm and Its Application in Big Data Modeling

Recent years, the application of big data model prediction in various fields has been increasing, but the improvement of model accuracy has always been a major problem. Integrating multiple base classifiers by using an ensemble algorithm is an efficient way to improve model accuracy. In this paper,...

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Veröffentlicht in:	2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) S. 1 - 6
Hauptverfasser:	Wang, Zhihong, Ren, Hongru, Lu, Renquan, Huang, Lirong
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 28.10.2022
Schlagworte:	Big Data Big Data Model Classification algorithms Data models Ensemble learning LightGBM-CatBoost-RandomForest Prediction algorithms Predictive models Stacking
Online-Zugang:	Volltext
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