Abstract
In this paper we introduce discriminant Q2 (DQ2) as an improvement for the Q2 value used in the validation of PLSDA models. DQ2 does not penalize class predictions beyond the class label value. With rigorous Monte Carlo simulations we show that when DQ2 is used, a smaller effect can be found statistically significant than when the standard Q2 is used. © The Author(s) 2008.
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APA
Westerhuis, J. A., van Velzen, E. J. J., Hoefsloot, H. C. J., & Smilde, A. K. (2008). Discriminant Q2 (DQ2) for improved discrimination in PLSDA models. Metabolomics, 4(4), 293–296. https://doi.org/10.1007/s11306-008-0126-2
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