How to determine what algorithm to apply in the following dataset (included)
Note that doing a dimensionality reduction with the target can lead you to the manifold problem. You can see in the image. What ends up happening is that the target information is lost.



The information that you provide is not enough to make a guess of what algorithm will be better.

Normally reducing the dimensionality of the problem to a lower dimension space in order to plot where you want to have the decision boundaries is not a good idea.

It's really hard to have a human understanding of how do these algorithms do the decision boundaries in a large scale dimension, that is why it is just better to have an empirical approach. Try a few of them, select a metric, and choose the one that has a higher score.