Thanks a lot for the presentation. It is really an interesting idea to use supervised learning methods combined with information of fundraising activity to predict voting behavior. In the conclusion part, you mentioned that there is limitation of supervised learning. Apart from kernel regularized least squares, is there any causal inference methods that could be taken advantage of to improve interpretability? Besides, is there any restriction of using the kernel regularized least squares method?
Thanks a lot for the presentation. It is really an interesting idea to use supervised learning methods combined with information of fundraising activity to predict voting behavior. In the conclusion part, you mentioned that there is limitation of supervised learning. Apart from kernel regularized least squares, is there any causal inference methods that could be taken advantage of to improve interpretability? Besides, is there any restriction of using the kernel regularized least squares method?