Effective techniques for intelligent cardiotocography interpretation using XGB-RF feature selection and stacking fusion-Reference-Cited by-同舟云学术

Effective techniques for intelligent cardiotocography interpretation using XGB-RF feature selection and stacking fusion

Published:2021-12-09 Issue: Volume: Page:
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Container-title:2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
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Author:

Feng Junyuan,Liang Jincheng,Qiang Zihan,Li Xia,Chen Qinqun,Liu Guiqing,Hong Jiaming,Hao Zhifeng,Wei Hang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9669261/9669139/09669694.pdf?arnumber=9669694

Reference18 articles.

1. Determination of fetal state from cardiotocogram using LS-SVM with particle swarm optimization and binary decision tree;y?lmaz;Comput Math Methods Med,2013

2. State Statistical Bureau;Statistical Yearbook of China,2017

3. Applications of random forest feature selection for fine-scale genetic population assignment

4. Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier

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