Determination of the optimal number of PLS components based on the combination of cross-validation and RMD-MRCD-PCA weighting function
Partial least squares (PLS) regression is a very useful tool for the analysis of high dimensional data (HDD). Choosing the ideal number of PLS components is a vital step in developing the best model. The accuracy of the model will be affected if there are too many or too few PLS components being sel...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2025
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| Online Access: | http://journalarticle.ukm.my/26523/1/SSS%2016.pdf http://journalarticle.ukm.my/26523/ https://www.ukm.my/jsm/english_journals/vol54num11_2025/contentsVol54num11_2025.html |
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