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Systems Science & Control Engineering

An Open Access Journal

Volume 7, 2019 - Issue 1

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An improved relief feature selection algorithm based on Monte-Carlo tree search

Jianyang ZhengDepartment of Automation, Xiamen University, Xiamen, People’s Republic of China

https://orcid.org/0000-0002-4548-4753 View further author information

Hexing ZhuDepartment of Automation, Xiamen University, Xiamen, People’s Republic of ChinaView further author information

Fangfang ChangDepartment of Automation, Xiamen University, Xiamen, People’s Republic of ChinaView further author information

Yunlong LiuDepartment of Automation, Xiamen University, Xiamen, People’s Republic of ChinaCorrespondence[email protected]

https://orcid.org/0000-0001-8448-7845 View further author information

Pages 304-310 | Received 25 Feb 2019, Accepted 26 Aug 2019, Published online: 05 Sep 2019

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https://doi.org/10.1080/21642583.2019.1661312
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Citations (4)

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Articles from other publishers (4)

Kaifang Wan, Jianmei Wang, Bo Li, Daqing Chen & Linyu Tian. (2022) Object feature selection under high-dimension and few-shot data based on three-way decision. The Visual Computer 39:6, pages 2261-2275.
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Halah Almazrua & Hala Alshamlan. (2022) A Comprehensive Survey of Recent Hybrid Feature Selection Methods in Cancer Microarray Gene Expression Data. IEEE Access 10, pages 71427-71449.
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Ying Li, Guohe Li & Lingun Guo. (2021) Feature Selection for Regression Based on Gamma Test Nested Monte Carlo Tree Search. Entropy 23:10, pages 1331.
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Muhammad Umar Chaudhry, Muhammad Yasir, Muhammad Nabeel Asghar & Jee-Hyong Lee. (2020) Monte Carlo Tree Search-Based Recursive Algorithm for Feature Selection in High-Dimensional Datasets. Entropy 22:10, pages 1093.
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