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- W2077975820 abstract "This paper presents a modified version of the NIPALS algorithm for PLS regression with one single response variable. This version, denoted a CF-PLS, provides significant advantages over the standard PLS. First of all, it strongly reduces the over-fit of the regression. Secondly, R2 for the null hypothesis follows a Beta distribution only function of the number of observations, which allows the use of a probabilistic framework to test the validity of a component. Thirdly, the models generated with CF-PLS have comparable if not better prediction ability than the models fitted with NIPALS. Finally, the scores and loadings of the CF-PLS are directly related to the R2, which makes the model and its interpretation more reliable. Copyright © 2011 John Wiley & Sons, Ltd." @default.
- W2077975820 created "2016-06-24" @default.
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- W2077975820 date "2011-02-10" @default.
- W2077975820 modified "2023-09-25" @default.
- W2077975820 title "Cross fitted partial least squares (CF-PLS): an alternative algorithm for a more reliable PLS" @default.
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- W2077975820 doi "https://doi.org/10.1002/cem.1380" @default.
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