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* formal errors - these are based on rules we have established (Energy not > 3700 kJ, etc);
 
* formal errors - these are based on rules we have established (Energy not > 3700 kJ, etc);
 
* interpreted errors - these are due to our understanding of the formal errors and are therefore more precise: kJ/kcal inverted, polyols missing, etc;
 
* interpreted errors - these are due to our understanding of the formal errors and are therefore more precise: kJ/kcal inverted, polyols missing, etc;
* outlier errors - data points that outside a formal nutritional envelope of a (cleaned) category of products. We can subdivide these into values that are impossible (very large outliers) and strange (can not be correct);
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* outlier errors - data points that outside a formal nutritional envelope of a (cleaned) category of products;
   −
Next question is what to do? Do we intervene, either by correcting or deleting? In any case we should inform the user what we did.
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Next question is what to do? Do we intervene, either by correcting or deleting? In any case we should inform the user what we did. I used to delete and/or correct, but now I feel this is not the right approach. We can only make a statement like: the producer value is too small/large (low/high?), (if the product has been correctly categorised and the nutritional table image corresponds correctly corresponds to the category) the value should lie between V<sub>lower</sub> and V<sub>upper</sub>.
    
== Graphing ==
 
== Graphing ==
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