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L. Xu, Q.-S. Xu, M. Yang, H.-Z. Zhang, C.-B. Cai, J.-H. Jiang, H.-L. Wu and R.-Q. Yu On estimating model complexity and prediction errors in multivariate calibration: generalized resampling by random sample weighting (RSW) Journal of Chemometrics 25

Version of Record online: 18 JUL 2010 | DOI: 10.1002/cem.1323

A generalized resampling method, random sample weighting (RSW) is proposed to estimate the number of PLS components. Random non-negative weights are assigned to the original training samples and a sample-weighted PLS model is developed without increasing the computational burden much. For prediction, only the training samples with random weights less than a threshold value are selected to ensure that the prediction samples have less influence on training.

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