Hi, here is my question: I trained a series of classifiers using Matlab Classification Learner and then I tried to replicate the same results writing my own code. I'm pretty sure I set all the parameters exactly the same way and used the same functions. I checked by generating code from the Classification Learner and making sure that my code had the same parameters. Now the thing is every time I train a model with the same data set, Matlab Classification Learner gives me the same accuracy, while when I do the same using my own code, the accuracy values change. This is due to the randomness associated with the cross validation step. So I assume that Matlab Classification Learner is running the cross validation step multiple time and then presenting the average accuracy of the cross validation. Am I right? Interestingly enough, if I use the code generated through the GUI and run it several times, even there the accuracy changes every time. So my question is how does the GUI get a constant accuracy? How many times does it average the cross validation results, if that's the case?