1

8 months AGO
views

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 …

4

1 year AGO
views

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…

1

1 year AGO
views

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.…

1

1 year AGO
views

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

2 years AGO
views

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.…

2

2 years AGO
views

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…

1

2 years AGO
views

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…

1

2 years AGO
views

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

2 years AGO
views

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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## Latest replies

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…

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…

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.…

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.…