Finding probability distributions associated with a cross-validated svm using bayesopt

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RIDDHIMAN LAHA
RIDDHIMAN LAHA 2018-3-30
编辑： Don Mathis 2018-4-5
I am finding difficulty in computing the probability of the predictions after training a Support Vector Machine with kfold cross validation and optimizing the hyperparameters using Bayesian optimization.
This is the code I am using
data = [S' U']'; size1 = size(S,1); size2 = size(U,1); theclass = ones((size1+size2),1); theclass(size1+1:end) = -1;
%% Preparing Cross Validation
c = cvpartition((size1+size2),'KFold',100);
%% Optimizing the SVM Classifier
opts = struct('Optimizer','bayesopt','ShowPlots',true,'CVPartition',c,... 'AcquisitionFunctionName','expected-improvement-plus');
svm = fitcsvm(data,theclass,'KernelFunction','rbf',... 'OptimizeHyperparameters','auto','HyperparameterOptimizationOptions',opts)
Any help is appreciated

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回答（1 个）

Don Mathis
Don Mathis 2018-4-5
编辑：Don Mathis 2018-4-5
To get posterior probabilities on a test set using a trained SVM, you can consult this Documentation page:
https://www.mathworks.com/help/stats/fitsvmposterior.html#bt72b34-1

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