writer：Xihui Bian*, Pengyao Diwu, Yirui Liu, Peng Liu, Qian Li, Xiaoyao Tan
keywords：Ensemble modeling, Multivariate calibration, Spectral analysis, Complex samples
source：期刊
specific source：Journal of Chemometrics, 2018, 32(11) e.2940
Issue time：2018年
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 sub-models. The generation
and calibration of the training subsets, as well as the integration of the
sub-models are three keys to the success of ensemble calibration. Many training
subset generating and sub-model 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.