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PCA/ CROSS-VALIDATION
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Hello! I have one question to you. PCA is usually not validated alrorithn beacase it is not a learning method. How does PCA use cross-validation and why is that?…
Equation for PLSR
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I have successfully performed Partial least squares regression. From here, how do I go about generating an equation?…
How to calculate Y residual variance of Factor 0 for PLS cross validation regression ?
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How to calculate Y residual variance of factor 0 for PLS cross validation in Unscramber software?…
beta coefficients and Prediction
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I find that PLS prediction using calibration model was the same (or very similar) as computation (prediction) using beta coefficients obtained from the same calibration model only for mean-centering modeling (or other regression models as well) only when without any preprocessing. However, when I ad…
How to determine the optimal factor of PLS model
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Just like I provided the Y explained variance of cross validation. The optimal factor is 8 that The Unscrambler gave. I want to know how to determine the optimal factor by calculation algorithm not by eyes. Thank you very much. Xudong  …
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Regarding to PLSR calibration of concentrations from NIR spectra, Let say, there are measurements at 200 wavelengths, then how many concentration measurements is suitable mathematically ? Minimum number, maximum number, optimal number. Please assume there are no colineaity problem. For example, is e…
ratio of calibrated to validate residual variance
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Dear All,   I\’m doing PLS Model and have message ratio of calibrated to validate residual variance for 3 factor. what does it mean and how I can manage it?   Thank you in advance.…
absorbance or reflectance? When should each of them be used?
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I have been doing PLS analysis on NIR spectroscopy of apple and egg. In both cases absorbance are used in the Y-axis and Wavelength in X-axis. In NIR diagram of raw data, What are absorbance, reflectance? When should each of them be used? What is the physical meaning of absorbance for apple sweetnes…
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Unscrambler HSI is a stand-alone product for simple and intuitive offline analysis of Hyperspectral Images (HSI). Unscrambler HSI allows you to explore and classify images using multivariate methods. If you have been using Unscrambler, you will be familiar with the tools in Unscrambler HSI.…
HSI Imageanalysis unscrambler UnscramblerHSI
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Unscrambler HSI is used for explorative, multivariate analysis of HSI data in the spectral domain using PCA and PLS-DA. Also SIMCA and PLS-DA classification is supported. More methods will be added based on customer needs.…
HSI Imageanalysis PCA PLS-DA principal component analysis SIMCA UnscramblerHSI

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External Admin
Case 2 is correct.…
Asya
The program will calculate: 1 case, average PC values were calculated for some groups of cross-validation (for example 4 segments), 2 case, the PC values is formed after the PCA of all samples, and the results of cross-validation are used only as s…
External Admin
The idea behind validation is that you use samples not used for building the model to test the model, so in theory validation does not affect the calculation of model parameters, such as scores. In the case of cross validation, the calibration sam…
Asya
Do I understand correctly, i.e. validation samples are not used to build a PCA model (in the process of separation the residuals matrix or as stopping criteria in the NIPALS algorithm). Cross-validation samples do not change the scores plot, right? …

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