Research on Hybrid Feature Selection Method Based on Iterative Approximation Markov Blanket
Joint Authors
Du, Jianqiang
Xu, Guo-Liang
Huang, Canyi
Nie, Bin
Xiong, Wangping
Li, Keding
Luo, Jigen
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-07
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The basic experimental data of traditional Chinese medicine are generally obtained by high-performance liquid chromatography and mass spectrometry.
The data often show the characteristics of high dimensionality and few samples, and there are many irrelevant features and redundant features in the data, which bring challenges to the in-depth exploration of Chinese medicine material information.
A hybrid feature selection method based on iterative approximate Markov blanket (CI_AMB) is proposed in the paper.
The method uses the maximum information coefficient to measure the correlation between features and target variables and achieves the purpose of filtering irrelevant features according to the evaluation criteria, firstly.
The iterative approximation Markov blanket strategy analyzes the redundancy between features and implements the elimination of redundant features and then selects an effective feature subset finally.
Comparative experiments using traditional Chinese medicine material basic experimental data and UCI’s multiple public datasets show that the new method has a better advantage to select a small number of highly explanatory features, compared with Lasso, XGBoost, and the classic approximate Markov blanket method.
American Psychological Association (APA)
Huang, Canyi& Li, Keding& Du, Jianqiang& Nie, Bin& Xu, Guo-Liang& Xiong, Wangping…[et al.]. 2020. Research on Hybrid Feature Selection Method Based on Iterative Approximation Markov Blanket. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1139610
Modern Language Association (MLA)
Huang, Canyi…[et al.]. Research on Hybrid Feature Selection Method Based on Iterative Approximation Markov Blanket. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1139610
American Medical Association (AMA)
Huang, Canyi& Li, Keding& Du, Jianqiang& Nie, Bin& Xu, Guo-Liang& Xiong, Wangping…[et al.]. Research on Hybrid Feature Selection Method Based on Iterative Approximation Markov Blanket. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1139610
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139610