A Combination Method of Resampling and Random Forest for Imbalanced Data Classification-Reference-Cited by-同舟云学术

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A Combination Method of Resampling and Random Forest for Imbalanced Data Classification

Published:2022-04-22 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Advances in Computer Technology, Information Science and Communications (CTISC)
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Author:

Zheng Liu¹,Han Qiu¹,Junhu Zhu¹

Affiliation:

1. Information & Engineering University,State Key Laboratory of Mathematical Engineering and Advanced Computing,Zhengzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9849705/9849682/09849803.pdf?arnumber=9849803

Reference15 articles.

1. When Is “Nearest Neighbor” Meaningful?

2. Random Forests[J];breiman;Machine Learning,2001

3. Diversity analysis on imbalanced data sets by using ensemble models

4. lmproved Random Forest Classification Algorithm for lmbalance Data Based on Hybrid Sampling Strategy[J];jianhua;Journal of Chongqing University of Technology (Natural Science),2019

5. Improved Random Forest Imbalance Data Classification Algorithm Combining Cascaded Upsampling and Downsampling [J];jianhua;Computer Science,2021

Cited by 1 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. Comparison of Ensemble Models as Solutions for Imbalanced Class Classification of Datasets;2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM);2023-01-03

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