Optimization of Classification Rules and Voting Strategies for Random Forest
Author:
Affiliation:
1. Jinan University,Guangzhou,China,510632
2. South China Agricultural University,Guangzhou,China,510642
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9754526/9754527/09754599.pdf?arnumber=9754599
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4. Fault diagnosis of a rolling bearing using wavelet packet denoising and random forests;ziwei;IEEE Sensors Journal,2017
5. A data-driven design for fault detection of wind turbines using random forests and xgboost;dahai;IEEE Access,2018
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