I am studying individual differences by doing mvpa for each ROI of each individual subject. I need some suggestions on feature selection. For now, I am just using univariate feature selection with cross-validation. I have 3 related questions:
I know there are several different feature selection strategies to use. I’m wondering what are the pros and cons of each of the strategy in my case?
In one of the previous posts, it is recommended to select the same amount of voxels in each ROI for better comparison. How necessary is that? If I have to do that, where in the algorithm should this be added? Could anyone give me a script example?
How necessary it is to use regularization after feature selection?