An Variable Selection Method of the Significance Multivariate Correlation Competitive Population Analysis for Near-Infrared Spectroscopy in Chemical Modeling

The high dimensionality of spectral datasets makes it difficult to select the optimal subset of variables. This paper presents a new method for variable selection called the significant multivariate competitive population analysis (SMCPA), Which combines ideas of significant multivariate correlation...

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Bibliographic Details
Main Authors: Yuxi Wang, Zhenhong Jia, Jie Yang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8905999/