Novel comprehensive variable selection algorithm based on multi-weight vector optimal selection and bootstrapping soft shrinkage | |
Pengfei Zhang4; Zhuopin Xu3,4; Huimin Ma2; Weimin Cheng3,4; Xiaohong Li3,4; Liwen Tang2,4; Guangxia Zhao3,4; Yuejin Wu1,4; Zan Liu4; Qi Wang1,4 | |
刊名 | Infrared Physics and Technology |
2023-06-25 | |
关键词 | Chemometrics Variable selection Near-infrared spectroscopy |
ISSN号 | 1350-4495 |
DOI | doi.org/10.1016/j.infrared.2023.104800 |
产权排序 | 1 |
英文摘要 | The dimensionality of spectral data is increasing with the advancements in spectral technology. Therefore, there is an urgent need to develop high-performance variable selection algorithms for chemometrics applications. This study proposes a novel multi-weight optimal-bootstrap soft shrinkage (MWO-BOSS) method for variable selection based on the bootstrap soft shrinkage (BOSS) algorithm, comprising three effective improvement strategies. First, the optimal weight vector of six weight vectors are used as weights of the selection variables, rather than the absolute value of the regression coefficients based only on a single weight vector. Second, in each loop, a step-by-step strategy is implemented to determine the optimal set of variables. Finally, a smoothing operation is added to the weight vector to improve the anti-noise performance of the algorithm. The performance of the MWO-BOSS algorithm was tested on the four spectral datasets corn protein, corn oil, soil, and beer and compared with six high-performance algorithms, namely interval partial least squares (iPLS), Moving Window Partial Least-Squares(MWPLS), competitive adaptive reweighted sampling (CARS), variable combinatorial population analysis |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/133257] |
专题 | 中国科学院合肥物质科学研究院 |
通讯作者 | Zan Liu; Qi Wang |
作者单位 | 1.Hainan Branch of the CAS Innovative Academy for Seed Design, Sanya 572025, China 2.Anhui Agricultural University, Hefei 230036, China 3.University of Science and Technology of China, Hefei 230026, China 4.Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China |
推荐引用方式 GB/T 7714 | Pengfei Zhang,Zhuopin Xu,Huimin Ma,et al. Novel comprehensive variable selection algorithm based on multi-weight vector optimal selection and bootstrapping soft shrinkage[J]. Infrared Physics and Technology,2023. |
APA | Pengfei Zhang.,Zhuopin Xu.,Huimin Ma.,Weimin Cheng.,Xiaohong Li.,...&Qi Wang.(2023).Novel comprehensive variable selection algorithm based on multi-weight vector optimal selection and bootstrapping soft shrinkage.Infrared Physics and Technology. |
MLA | Pengfei Zhang,et al."Novel comprehensive variable selection algorithm based on multi-weight vector optimal selection and bootstrapping soft shrinkage".Infrared Physics and Technology (2023). |
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