Ensemble calibration for the spectral quantitative analysis of complex samples

Skip to Navigation

EarlyView Article

  • Published: Oct 17, 2017
  • Author: Xihui Bian, Pengyao Diwu, Yirui Liu, Peng Liu, Qian Li, Xiaoyao Tan
  • Journal: Journal of Chemometrics

Abstract

Ensemble strategies have gained increasing attention in multivariate calibration for quantitative analysis of complex samples. The aim of ensemble calibration is to obtain a more accurate, stable, and robust prediction by combining the predictions of multiple submodels. The generation and calibration of the training subsets, as well as the integration of the submodels, are three keys to the success of ensemble calibration. Many training subset generating and submodel integrating strategies have been developed to form numerous ensemble calibration methods for improving the performance of the basic calibration method. This contribution focuses on the recent ensemble strategies in relation to calibration, especially the ensemble modeling for quantitative analysis of complex samples. The limitations and perspectives of ensemble strategies are also discussed.

Social Links

Share This Links

Bookmark and Share

Microsites

Suppliers Selection
Societies Selection

Banner Ad

Click here to see
all job opportunities

Most Viewed

Copyright Information

Interested in spectroscopy? Visit our sister site spectroscopyNOW.com

Copyright © 2017 John Wiley & Sons, Inc. All Rights Reserved