Plotting ROC for fitcecoc svm classifier
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Hi I have created a 4 level SVM classifier by fitcecoc. I need to generate ROC curve for each class. This is the code: template = templateSVM('KernelFunction', 'gaussian', 'PolynomialOrder', [], ... 'KernelScale', 1, 'BoxConstraint', 1, 'Standardize', true);
[classificationSVM,HyperparameterOptimizationResults] = fitcecoc(predictors... , response, 'Learners', template, 'Coding', 'onevsone', 'OptimizeHyperparameters',... {'BoxConstraint','KernelScale'},'HyperparameterOptimizationOptions',... struct('AcquisitionFunctionName', 'expected-improvement-plus',... 'Repartition',true,'MaxObjectiveEvaluations',10,'kfold',5),'Verbose',0,... 'FitPosterior',1);
[label,NegLoss,PBScore,Posterior] = resubPredict(classificationSVM);
Apparently, I need to use perfcurve function to get the ROC. Yet, the help instructions are for fitcsvm that does not work for fitcecoc. I am trying to use the following code for class 1: [Xsvm,Ysvm,Tsvm,AUCsvm] = perfcurve(response,Posterior(:,1),'true'); Yet, I receive the below error message: Error using perfcurve>membership (line 693) Positive class is not found in the input data.
Error in perfcurve (line 437) [W,subYnames] = membership(cls(sorted),weights(sorted),... I was wondering how I can proceed from here.
Thanks, Roohollah
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SI LIU
2021-4-27
Undefined function 'Posterior' for input arguments of type 'ClassificationECOC'.
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Prashant Arora
2017-10-18
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Hi Roohollah,
The reason you are getting this error because you defined the positive class to be "true" in the perfcurve function. This only work if the labels are logical values, i.e. can be defined as "true" or "False". If your labels are not logical values, you must define the Positive class as one of the member of the labels. You can find more information about this at the following link:
Hope this helps!
Prashant
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