Near infrared spectral variable optimization by final complexity adapted models combined with uninformative variables elimination-a validation study
作者： Xiangzhong Song , Yue Huang , Kuangda Tian , Shungeng Min
DOI: 10.1016/J.IJLEO.2019.164019
关键词:
摘要: Abstract A combination method for spectral variable selection was proposed in this study. In method, predictive property ranked reduction with final complexity adapted models (FCAM) used further refinement following of uninformative variables elimination (UVE). practice, two different near infrared (NIRS) datasets were investigated to evaluate the quantitative performance method. Results showed that UVE-FCAM selected much fewer better prediction than single UVE on both datasets. Moreover, by contrast, and modeling stability proved be a widely-used as UVE-SPA. Overall results demonstrated could promising alternative optimizing variables, FCAM had potential an effective other methods.
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