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CARS-PLS
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By employing the simple but effective principle ‘survival of the fittest’ on which Darwin’s Evolution Theory is based, a novel strategy for selecting an optimal combination of key wavelengths of multi-component spectral data, named Competitive Adaptive Reweighted Sampling (CARS), is developed. Key wavelengths are defined as the wavelengths with large absolute coefficients in a multivariate linear regression model, such as partial least squares (PLS).The absolute values of regression coefficients of PLS model are used as an index for evaluating the importance of each wavelength. Then, based on the importance level of each wavelength, CARS sequentially selects N subsets of wavelengths from N Monte Carlo (MC) sampling runs in an iterative and competitive manner. In each sampling run, a fixed ra
文 件 列 表
CARS
CARS_manual.doc
carspls.m
CIP2pred.m
classplot2.m
compute_T2DM_data.asv
corn_m51.mat
csvd.m
databin.m
dosc.M
example_nir.m
expred1.m
expred2.m
ks.m
LOGO_CARS.JPG
lsreg.m
Manne_bi.m
mcs.m
mcuvepls.m
mwpls.m
oscplscv.m
plotcars.m
plotmcs.m
pls.m
pls_nipals.m
plscvfold.m
plsdcv.m
plsmccv.m
plsnipals.m
plsrdcv.m
plssim.m
plsval.m
pretreat.m
rswrw.m
scarspls.asv
scarspls.m
simuin.m
test_package_functions.m
test_script_rce.m
tp.m
traintestselect.m
variableSetComparion.m
vipp.m
