Teaching as a practice: A rejoinder

Pearson, Allen T.

doi:10.1007/bf01075825

Cited by 2 publications

(2 citation statements)

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“…As an objective criterion for the success of the pre‐processing, we will use partial least squares regression (PLSR) combined with cross‐validation . PLSR decomposes the calibration data to create a component‐based representation of the data similar to PCA . The difference between PCA and PLS is that the former maximises the variation of the predictors per component, while PLS maximises the predictors' covariance to the response per component.…”

Section: Methodsmentioning

confidence: 99%

Model‐based pre‐processing in Raman spectroscopy of biological samples

Liland

Köhler

Afseth

2016

J. Raman Spectrosc.

101

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a Model-based pre-processing has become wide spread in spectroscopy and is the standard procedure in Fourier-transform infrared spectroscopy. It has also been shown to give valuable contributions in Raman spectroscopy. Extended multiplicative signal correction is flexible enough to handle varying fluorescence background and take into account individual variations in baselines while still keeping enough rigidity through reference spectra and model fitting to avoid degenerate solutions and overfitting, when used correctly. We demonstrate the basic extended multiplicative signal correction method and some extensions, including a novel shift correction, on real Raman data to demonstrate effects on visual appearance, replicate variation and prediction. Comparisons with other standard correction methods are also shown and discussed.

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Section: Methodsmentioning

confidence: 99%

Model‐based pre‐processing in Raman spectroscopy of biological samples

Liland

Köhler

Afseth

2016

J. Raman Spectrosc.

101

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show abstract

“…However, in certain cases such as cardiac motion, 19,20 where tissue deformations are complex, other approaches for quantifying the displacement and strain may be necessary. 35 Principal component analysis ͑PCA͒ 36,37 is another method for characterizing the strain distribution where the primary strain tensor components may not lie along the ultrasound insonification direction. Principal strains are defined as the normal strain components along the deformation axes where the shearing strains are included in principal strains.…”

Section: Introductionmentioning

confidence: 99%