Zobrazeno 1 - 10 of 26 156 pro vyhledávání: '"ensemble machine learning"'
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Akademický článek
Ensemble machine learning framework for predicting maternal health risk during pregnancy.
Autor: Khadidos, Alaa O.1,2 (AUTHOR), Saleem, Farrukh3 (AUTHOR), Selvarajan, Shitharth4,5 (AUTHOR) shitharths@kdu.edu.et, Ullah, Zahid6 (AUTHOR), Khadidos, Adil O.7 (AUTHOR)
Publikováno v: Scientific Reports. 9/14/2024, Vol. 14 Issue 1, p1-20. 20p.
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5
Akademický článek
An Ensemble Machine Learning Approach for Sea Ice Monitoring Using CFOSAT/SCAT Data.
Autor: Luo, Yanping1 (AUTHOR) luoyanping@stu.ouc.edu.cn, Liu, Yang1 (AUTHOR) yangliu315@ouc.edu.cn, Huang, Chuanyang1 (AUTHOR), Han, Fangcheng1 (AUTHOR)
Publikováno v: Remote Sensing. Sep2024, Vol. 16 Issue 17, p3148. 31p.
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6
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Shifting from endangerment to rebirth in the Artificial Intelligence Age: An Ensemble Machine Learning Approach for Hawrami Text Classification
Autor: Khaksar, Aram, Hassani, Hossein
Hawrami, a dialect of Kurdish, is classified as an endangered language as it suffers from the scarcity of data and the gradual loss of its speakers. Natural Language Processing projects can be used to partially compensate for data availability for en
Externí odkaz: http://arxiv.org/abs/2409.16884
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7
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Introducing Ensemble Machine Learning Algorithms for Automatic Test Case Generation using Learning Based Testing
Autor: Rahman, Sheikh Md. Mushfiqur, Eisty, Nasir U.
Ensemble methods are powerful machine learning algorithms that combine multiple models to enhance prediction capabilities and reduce generalization errors. However, their potential to generate effective test cases for fault detection in a System Unde
Externí odkaz: http://arxiv.org/abs/2409.04651
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8
Akademický článek
Development of a risk prediction model for radiation dermatitis following proton radiotherapy in head and neck cancer using ensemble machine learning.
Autor: Lee, Tsair-Fwu1,2,3 (AUTHOR), Liu, Yen-Hsien1 (AUTHOR), Chang, Chu-Ho1 (AUTHOR), Chiu, Chien-Liang1 (AUTHOR), Lin, Chih-Hsueh1 (AUTHOR), Shao, Jen-Chung1 (AUTHOR), Yen, Yu-Cheng1 (AUTHOR), Lin, Guang-Zhi1 (AUTHOR), Yang, Jack4 (AUTHOR), Tseng, Chin-Dar1 (AUTHOR), Fang, Fu-Min5 (AUTHOR), Chao, Pei-Ju5 (AUTHOR) pjchao99@gmail.com, Lee, Shen-Hao1,6 (AUTHOR) leeshenhao@gmail.com
Publikováno v: Radiation Oncology. 6/24/2024, Vol. 19 Issue 1, p1-11. 11p.
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9
Akademický článek
A Novel Strategy Coupling Optimised Sampling with Heterogeneous Ensemble Machine-Learning to Predict Landslide Susceptibility.
Autor: Lu, Yongxing1 (AUTHOR) luyongxing@mail.cgs.gov.cn, Xu, Honggen1 (AUTHOR) xuhonggen@mail.cgs.gov.cn, Wang, Can2 (AUTHOR) canwang_hndzgczx@163.com, Yan, Guanxi3 (AUTHOR) guanxi.yan@uqconnect.edu.au, Huo, Zhitao1 (AUTHOR) huozhitao@mail.cgs.gov.cn, Peng, Zuwu4 (AUTHOR), Liu, Bo3,5 (AUTHOR) lbo@hhu.edu.cn, Xu, Chong6 (AUTHOR) chongxu@ninhm.ac.cn
Publikováno v: Remote Sensing. Oct2024, Vol. 16 Issue 19, p3663. 32p.
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Logifold: A Geometrical Foundation of Ensemble Machine Learning
Autor: Jung, Inkee, Lau, Siu-Cheong
We present a local-to-global and measure-theoretical approach to understanding datasets. The core idea is to formulate a logifold structure and to interpret network models with restricted domains as local charts of datasets. In particular, this provi
Externí odkaz: http://arxiv.org/abs/2407.16177
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