A simple idea on applying large regression coefficient to improve the genetic algorithm-PLS for variable selection in multivariate calibration
作者： Yong-Huan Yun , Dong-Sheng Cao , Min-Li Tan , Jun Yan , Da-Bing Ren
DOI: 10.1016/J.CHEMOLAB.2013.09.007
关键词:
摘要: Abstract Genetic algorithm-based couple with partial least squares (PLS) has been successfully applied for variable selection in multivariate calibration. On the basis of fact that a large PLS regression coefficient indicates an important variable, new and simple idea structure proportion chromosomes initial population is determined by presented this study. The obtained establishing modeling on autoscaled data. With improved approach, modified GA-PLS method not only makes optimization better toward optimal solution, but also obeys rule GAs. results through investigating one simulated dataset two near infrared show made much improvement compared to original GA-PLS.
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