Averaging and stacking partial least squares regression models to predict the chemical compositions and the nutritive values of forages from spectral near infrared data

HIGHLIGHTS

• who: Mathieu Lesnoff and collaborators from the Institut Agro, France University Clermont Auvergne, VetAgro Sup, UMR Herbivores have published the Article: Averaging and Stacking Partial Least Squares Regression Models to Predict the Chemical Compositions and the Nutritive Values of Forages from Spectral Near Infrared Data, in the Journal: (JOURNAL)
• what: The paper focuses on an alternative bypassing the determination of the PLSR dimensionality and allowing for automatizing the predictions. The paper presents various methods of PLSR and and compares their performances to the usual PLSR on six real datasets on different types of forages. Other . . .
  

   

  

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