An ensemble of Monte Carlo uninformative variable elimination for wavelength selection
An ensemble of Monte Carlo uninformative variable elimination for wavelength selection
复制标题
用于波长选择的蒙特卡罗无信息变量消除的集合
DOI：
10.1016/j.aca.2008.02.032
复制
发表时间：
2008-04-01
影响因子：
6.2
通讯作者：
Yu, Ru-Qin
中科院分区：
文献类型：
--
作者：
Han, Qing-Juan;Wu, Hai-Long;Yu, Ru-Qin
An improved method based on an ensemble of Monte Carlo uninformative variable elimination (EMCUVE) is presented for wavelength selection in multivariate calibration of spectral data. The proposed algorithm introduces Monte Carlo (MC) strategy to uninformative variable elimination-PLS (UVE-PLS) instead of leave-one-out strategy for estimating the contributions of each wavelength variable in the PLS model. In EMCUVE wavelength variables are evaluated by different Monte Carlo uninformative variable elimination (MCUVE) models. Moreover, a fusion of MCUVE and the vote rule can obtain an improvement over the original uninformative variable elimination method. Results obtained from simulated data and real data sets demonstrate that EMCUVE can properly carry out wavelength selection in the course of data analysis and improve predictive ability for multivariate calibration model. (C) 2008 Elsevier B.V. All rights reserved.
