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Hyperparameter Optimization in ECOC classifier: which loss function is used?

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Dear, I'm training an ECOC classifier using knn as the base classifier.
I would like to use the option 'OptimizeHyperparameters','auto' to let fitcecoc apply leave one out cross validation the best Coding, NumNeighbors, distace parameters.
tknn = templateKNN();
mdlknnCecoc = compact(fitcecoc(XKnn,labelsRed, ...
'OptimizeHyperparameters','all', ...
'HyperparameterOptimizationOptions',struct( 'UseParallel',...
true,'CVPartition',c), 'Learners',tknn));
In MATLAB help I read: " The optimization attempts to minimize the cross-validation loss (error) for fitcecoc by varying the parameters."
However, which loss function is used? I found no detail about that.

Accepted Answer

Don Mathis
Don Mathis on 20 Sep 2019
it says
"The optimization attempts to minimize the cross-validation loss (error) for fitcecoc by varying the parameters. For information about cross-validation loss in a different context, see Classification Loss. "
If you click on "Classification Loss" it tells you about the multiclass loss function.
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