An efficient variable selection method based on random frog for the multivariate calibration of NIR spectra
نویسندگان
چکیده
منابع مشابه
An efficient method of wavelength interval selection based on random frog for multivariate spectral calibration.
Wavelength selection is a critical step for producing better prediction performance when applied to spectral data. Considering the fact that the vibrational and rotational spectra have continuous features of spectral bands, we propose a novel method of wavelength interval selection based on random frog, called interval random frog (iRF). To obtain all the possible continuous intervals, spectra ...
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Variable (or wavelength) selection plays an important role in the quantitative analysis of near-infrared (NIR) spectra. A modified method of uninformative variable elimination (UVE) was proposed for variable selection in NIR spectral modeling based on the principle of Monte Carlo (MC) and UVE. The method builds a large number of models with randomly selected calibration samples at first, and th...
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چکیده ندارد.
Selection of a Multivariate Calibration Method
1. Methods to be considered for multivariate calibration Many methods for multivariate calibration have been proposed. It turns out that many of the methods perform similarly. To avoid confusion due to use of many different methods, it is suggested that only the following should be considered: Multiple linear regression (MLR) Principal component regression (PCR) Partial least squares (PLS) Neur...
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In a growing number of domains the data collected has a large number of features. This poses a challenge to classical pattern recognition techniques, since the number of samples often is still limited with respect to the feature size. Classical pattern recognition methods suffer from the small sample size, and robust classification techniques are needed. In order to reduce the dimensionality of...
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ژورنال
عنوان ژورنال: RSC Advances
سال: 2020
ISSN: 2046-2069
DOI: 10.1039/d0ra00922a