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Why almost the same optimization function gives different results?

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Nadou on 16 Jul 2021
Commented: Nadou on 19 Jul 2021
I am trying to optimize ECOC classifier as follows:
clear all
load fisheriris
X = meas;Y = species;
rng default
Mdl_gaussian = fitcecoc(X,Y,'Coding','onevsall','Learners',t_gaussian,'OptimizeHyperparameters','auto',...
I am wondering why I did not find the same results if I remplace 'OptimizeHyperparameters','auto' with 'OptimizeHyperparameters',{'BoxConstraint','KernelScale'}
rng default
Mdl_g = fitcecoc(X,Y,'Coding','onevsall','Learners',t_gaussian,'OptimizeHyperparameters',{'BoxConstraint','KernelScale'},...
Best regards

Answers (1)

Alan Weiss
Alan Weiss on 16 Jul 2021
Edited: Alan Weiss on 18 Jul 2021
I am not 100% sure, but my reading of the fitcecoc documentation shows that 'auto' has this description:
'auto' — Use {'Coding'} along with the default parameters for the specified Learners:
  • Learners = 'svm' (default) — {'BoxConstraint','KernelScale'}
So I think that 'auto' is equivalent to {'Coding','BoxConstraint','KernelScale'}.
Alan Weiss
MATLAB mathematical toolbox documentation
  1 Comment
Nadou on 19 Jul 2021
Hello Alan,
Thank you for your response
This is what I thought also while reading fitcecoc documentation. However, I found different results
Best regards

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