What is the different between BER and PRESS in PLSDA?

The determination of the number of component in the PLS-DA model based on balanced error rate (BER)? what is the different between BER and predicted residual sum of squares (PRESS) in PLS?


Hi @aurum,

How BER is calculated: The classification error rate for each class is calculated. These values are then averaged to get a balanced error rate which gives all classes the same weight regardless of the number of samples in them. It is between 0 and 1 and a lower value indicates a rather accurate model. Tuning for BER ensures all classes are equally accounted for in the model fit.

PRESS: The residual sum of squares for the samples which were not used to fit the model. It can take any non-negative value. A lower value indicates a good fit. Tuning for PRESS helps avoid over-fitting.

Hope it helps.


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Thanks a lot. It really help to understand BER.