A new hyper-parameter optimization method for machine learning in fault classification-Reference-Cited by-同舟云学术

A new hyper-parameter optimization method for machine learning in fault classification

Published:2022-10-21 Issue: Volume: Page:
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Ye Xingchen,Gao Liang,Li Xinyu,Wen Long

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-04238-0.pdf

Reference50 articles.

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3. Xue Y, Zhang L, Wang B, Zhang Z, Li F (2018) Nonlinear feature selection using Gaussian kernel SVM-RFE for fault diagnosis. Appl Intell 48:3306–3331

4. Guo J, Yang L, Bie R, Yu J, Gao Y, Shen Y, Kos A (2019) An XGBoost-based physical fitness evaluation model using advanced feature selection and Bayesian hyper-parameter optimization for wearable running monitoring. Comput Netw 151:166–180

5. Klein A, Falkner S, Bartels S (2017) Fast bayesian optimization of machine learning hyper-parameters on large datasets. Artificial Intell Stat PMLR:528–536

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