'FitPosterior' option for fitcecoc

3 vues (au cours des 30 derniers jours)
Yoshihiro Yamada
Yoshihiro Yamada le 25 Août 2017
Commenté : Han zid le 19 Août 2018
I am evaluating SVM ('fitcecoc' function) by applying my data 'pm_pareto_12456'. When I set 'FitPosterior' option 'true', I encountered unexpected result described as follows: I execute prediction by using original data. when 'FitPosterior' option is false, the result is same as original classification 'class_array_12456', however, when 'FitPosterior' option is true, some elements of 'predicted_class_12456_true' are different from 'class_array_12456'. I wonder if 'FitPosterior' option could affect the prediction results?
SVM_data.mat contains variables for my evaluation and SVM_Test.m is evaluation script. P.S. my matlab version is 2017a

Réponses (1)

Carl
Carl le 29 Août 2017
Modifié(e) : Carl le 29 Août 2017
Hi Yoshihiro. See the documentation here for the 'FitPosterior' option in fitcecoc:
It mentions that when that option is set to true, it translates classification scores to posterior probabilities. The model will inherently use different values for its fitting and prediction. As you observed, this may end up with different results.
  2 commentaires
Yoshihiro Yamada
Yoshihiro Yamada le 30 Août 2017
Modifié(e) : Yoshihiro Yamada le 30 Août 2017
Hi Carl.
According to your advice, I should accept instability of predicted results. Therefore, I tried to change another option to avoid instability and it works well! Thank you for your advice.
Han zid
Han zid le 19 Août 2018
Hi Yoshihiro, I get to same probelem as yours , can you please help me with the option you used to solve this problem.

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