Stratified 10 fold cross validation on imbalanced dataset
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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.![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/622138/image.png)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/622138/image.png)
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
1 Commento
Yaser Awadh
il 7 Dic 2022
Hi, Could you please share with me the code. I have tried to download frm GD, but I could'nt.
Thank you
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