Stacking Based LightGBM-CatBoost-RandomForest Algorithm and Its Application in Big Data Modeling-Reference-Cited by-同舟云学术

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

Published:2022-10-28 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)
language:
Short-container-title:

Author:

Wang Zhihong¹,Ren Hongru¹,Lu Renquan¹,Huang Lirong¹

Affiliation:

1. Guangdong University of Technology,School of Automation and Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control,Guangzhou,China,510006

Funder

Research and Development

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9967441/9967479/09967714.pdf?arnumber=9967714

Reference16 articles.

1. Stock price prediction based on LSTM and LightGBM hybrid model

2. Numerical Forecast Correction of Temperature and Wind Using a Single-Station Single-Time Spatial LightGBM Method

3. Real-time hard-rock tunnel prediction model for rock mass classification using CatBoost integrated with Sequential Model-Based Optimization

4. Comparison of Statistical Logistic Regression and RandomForest Machine Learning Techniques in Predicting Diabetes

5. Stacking Model for Optimizing Subjective Well-Being Predictions Based on the CGSS Database

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. LightGBM-BES-BiLSTM Carbon Price Prediction Based on Environmental Impact Factors;Computational Economics;2024-06-27

2. Prediction of Stroke Probability by Data Analyzing and Model Training;2024 International Conference on Electrical Drives, Power Electronics & Engineering (EDPEE);2024-02-27

3. Soft sensor based on multi‐phase stacking ensemble model with self‐selected primary learner for batch processes;The Canadian Journal of Chemical Engineering;2023-11-05

4. Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study;2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom);2023-11-01