12 feb. 2018

To consider when validating with LOCAL

I talk in other posts about LOCAL calibration. Once the LOCAL model is placed for routine, and the time pass, is time for validation.
 
LOCAL may have several products merged in a unique database from which we have developed the calibration, so it is important to label every sample in the validation set with a value (in this case 1: Black, 2:Red and 3:Green) corresponding to 3 different types of pork meat meal.
 
The validation is just to compare the reference values from the laboratory and the predicted values from our Near Infrared Instrument in this case, and the best way to represent it is a XY plot. The constituents most important in meat meal are: Moisture, Protein, Fat and Ash.
 
A first look to the general XY plots will gives an idea how it works:
The plot tell us that we have to split the validation set into 3 validation sets one for every class to calculate the statistics for every one.
In the case of Protein we will get this validation:

For the Green product:
For the Red Product:
For the Black Product:

As we can see we have a significant Bias for product 1, but not for the other two products, so we can proceed with the validation adjustments (3 products linked to a LOCAL database, and one of them bias adjusted until the calibration is updated).
 
Plots with R
 
 

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