OPLS discriminant analysis: combining the strengths of PLS‐DA and SIMCA classification

M. Bylesjö, M. Rantalainen, O. Cloarec, J. Nicholson, E. Holmes, J. Trygg

2006 Journal of Chemometrics: A Journal of the Chemometrics Society Cited 1,379 times

Cited in this thesis

Introduction Fish Species and Part Identification Oil Contamination and Cross-Species Adulteration

Frequently Cited Together

One model to learn them allKaiser 20173 chapters
From Laboratory Exploration to Practice: Applications, Challenges, and DevelopmeXue 20253 chapters
Deep LearningGoodfellow 20163 chapters
Stacked generalizationWolpert 19923 chapters
Grad-cam: Visual explanations from deep networks via gradient-based localizationSelvaraju 20173 chapters
Bert: Pre-training of deep bidirectional transformers for language understandingDevlin 20183 chapters

BibTeX

@article{Bylesjoe2006,
  author = {Bylesjo, Max and Rantalainen, Mattias and Cloarec, Olivier and Nicholson, Jeremy K and Holmes, Elaine and Trygg, Johan},
  journal = {Journal of Chemometrics: A Journal of the Chemometrics Society},
  title = {OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification},
  year = {2006},
  number = {8-10},
  pages = {341–351},
  volume = {20},
  publisher = {Wiley Online Library},
}