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To simplify the calculations in this section, we do not count the number of errors on the test set when evaluating a classifier, but instead look at how well the classifier estimates the conditional probability of a document being in a class.
A number of sensor placement techniques are used in this study, and the comparison reveals that, for this system, the Modal TAM is twice as sensitive to errors on the test mode shapes when it is created on a sensor set optimized for the Static TAM rather than one that was optimized specifically for the Modal TAM.
The errors on the test and training set are in a similar range, which indicates that the models have a good ability to generalize.
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Further, the thermal material expansion error of the test piece on centric clamped machined workpieces can be evaluated with the new thermal test piece.
In Section 13.1 (page ), we said that we want to minimize classification error on the test set.
Training stops when the error on the test data fails to improve.
For the different aircraft types in our FDR dataset, the CART models give a lower prediction error on the test dataset as compared to the ICAO Engine Exhaust Emissions Databank.
The entire training process was stopped when the error on the test set was minimal, and this occurred when the normalized RMS curve with respect to the percentage miscalculation curve became flat.
We have recorded the number of distinct labels identified and the error on the test set for each iteration, for every combination of dataset, base classifier and query selection criteria.
However, estimates of prediction error on the test data set produce different results from those on the training set (Table 1).
Architectures with hidden neurons in the range 22 to 86 were tested, and the network with the highest prediction performance (lowest square error) on the test set was selected.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com