An Integration of Modified Uninformative Variable Elimination and Wavelet Packet Transform for Variable Selection

作者：Chen, Xiaojing; Wu, Di; He, Yong^*

来源：Spectroscopy (Santa Monica), 2011, 26(4): 42-47.

• PARTIAL LEAST-SQUARES
• NEAR-INFRARED SPECTROSCOPY
• FEATURE-EXTRACTION
• QUALITY
• IMPROVEMENT
• ALGORITHMS
• MODELS

The wavelet packet transform (WPT) combined with the modified uninformative variable elimination (MUVE) method (WPT-MUVE) is proposed to select variables for multivariate calibration of spectral data. In this approach, MUVE is used to select informative variables in the wavelet packet decomposition domain. The proposed method was applied to near-infrared (NIR) reflectance spectroscopy data for analysis of protein and fat in milk powder samples, and the performance was compared to full spectrum partial least squares (PLS), conventional uninformative variable elimination (UVE), and the MUVE method. Using the proposed method, a model with fewer variables and better prediction performance was obtained.

• 出版日期2011-4
• 单位浙江大学; 温州大学