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1
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I´m working with LDA in Unsc X ver 10.4 trying to classify samples with NIR spectral information. The LDA results obtain a prediction matrix with the discriminant value for each class. How calculate Unsc these discriminant values? At the same time, I would like to obtain the discriminant functions …
1
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How do I do batch wise unfolding in camo? how do I do multiway PLS ?  …
4
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I have an error message when i tried to run the scripst andrews curves. The column vegetable is not recognized. I got he following error message: PythonWorker |  ERROR: ‘Vegetable’ I would apprfeciate your helping me with that. Thanks…
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Hi everyone. Is there a way to obtain values of Cook’s distance in MLR? I am trying to identify influential observations by use of studentized residuals and Cook’s D statistics. This was kind of  advised procedure for a specific problem I am currently dealing with. Thanks in advance.…
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I tried making the model with SVMR on my data set having 75% as training set and rest for external prediction the R squared value for calibration and cross validation were quite good, but how to get the R squared value for the Prection data set, I also tried copying the results into excel and [&hell…
1
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Greeting. Please, which option in Uscramblr 10.3 gives me: Equal scale in PLS predicted vs. measured plot. (I prefer sometimes equal scale instead of auto scale sometimes). Thanks for your cooperation.…
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In a univariate experiment one can add  known amounts of an analyte to a sample. The equation of the linear regression line y=ax+b can then be extrapolated to where y=0. The concentration of the analyte is then equal to the absolute value of x. I like to use this method with near-infrared spectrome…
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Hello, Is it possible to do variable selection methods with the Unscrambler X program. I am working with ICP-MS data and want to calculate F-ratios for each element and subsequently perform degree of class separation to try and refine the elements i’m using within my PCA plots, for the purpose…
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Hello, is it possible to use a LDA directly on spectroscopic data without a PCA for data reduction? Does it make sense? In general there is always the combination PCA-LDA on spectroscopic data. In literature it is not usual just using the LDA directly. But are there any reasons besides the data redu…
3
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Hello, I have just begun to use Python script in Unscrambler 11, and I have created my first Random Forest Classification model. I have first crated the model with “RandomForestClassifierBuildModel”, then I applied it to data with RandomForestClassifierClassify”. Apparently all wen…

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External Admin
LDA as implemented in Unscrambler has three options. These are based on an estimation of the pooled covariance of the individual classes: . Linear . Quadratic . Mahalanobis distance. For the Linear and Quadratic option, prior probability may b…
LeslieMetrics
New python script for classification performance metrics is now available. This includes generation of a confusion matrix, accuracy, sensitivity, specificity, etc. Access it from here: https://community.camo.com/?p=2120#classification…
External Admin
Remember to include the category variable and the spectral variables when selecting the input for the script. The category variable must be named 'Vegetable' in the column header.…
External Admin
Camo offers an Unscrambler plug-in for analysis of batch data. If you want to do batch-wise PLS analysis, you first have to perform batch modelling using this plug-in to convert the data into relative time (to solve for the challenge of having batche…
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