Can anyone confirm whether or not the Classification Learner App uses Mean Square Error for performance?
My project has me comparing classification performances using Neural Networks (via patternnet) and Support Vector Machines (via classification learner app).
The documentation for patternnet says the performance accuracies are given in Mean Square Error (MSE). This is great that it is in the documentation.
On the other hand, the performance of the SVMs do not specificy whether they are MSE or Root Mean Square Error or something else. I would like to compare the performance of the models and I cannot do this if I cannot ensure they both are using MSE. I would like to assume that all the classification learner performances are given in MSE (as that might be the default).
Which leads me to my question: can anyone confirm whether or not the Classification Learner App uses Mean Square Error for performance?