Stratified 10 fold cross validation on imbalanced dataset

Hello,

I have a variable named 'Xfeat' which is of size 3816401x2 "Table" , It has 2 classes(Lables) 'hypopnea' and 'Normal' . It contains 6 features namely 'feat_mat_1' to 'feat_mat_1'

It is a hugely imbalanced dataset with number of hypopnea being so low(1:100)

Using the normal 10-fold cross validation(from classification learner app) and using RUS-boosted trees as classifier gives an accuracy around 60 percent.

People have suggested to use stratified 10-fold cross validation but I am unable to implement this in classification learner app.

I request someone familar in implementing these classifiers through code to help me implement this as a code(I am a newbie to coding)

Here's the link to the file https://drive.google.com/file/d/1p3_hYuTyX2_5HNunX9NmrIKOFKsIiBfR/view?usp=sharing

And this would also help many newbies like me on the internet as well as there are very few discussions on this topic and I also thank matlab community for being so quick to respond to my previous questions

Thank you

[Yaser Awadh]

Hi, Could you please share with me the code. I have tried to download frm GD, but I could'nt.

Thank you