The input hyperparameters for a Classifica​tionDiscri​minant classifier are different from those retrieved from the trained model

I am training a discriminant model using fitcdiscr function.

discrMdl = fitcdiscr(Xtrain,Ytrain,'discrimType','linear','ClassNames',{'1','2'},
    'Delta', Delta,'Gamma',Gamma);

After training, for double checking, the hypeparameters Gamma and Delta are retrived from

discrMdl.Delta 

and

discrMdl.Gamma

But they are different from those in the function arguments above. How does that happen?

I also note that the descriminant model, which was obtained by training the fitcdiscr with 'OptimizeHyperparameters' configured, is different from the retrained model with the identified hyperparameters (using: bestPoint(discrMdl.HyperparameterOptimizationResults)).

I wonder if the returned model for hyperparamters optimization is already the one trained with the optimal hyparameters, since there may be no need for model retraining.