# Finding optimal hyperplane

I have a set of vectors $\{V_i\}$ in $n$-dimensional space. There is a number corresponded to each vector $\alpha_i = f(V_i)$ ($\alpha_i$ can be negative). I want to find a hyperplane which would maximize the difference between sums of $\alpha_i$ on the different sides of the space, divided by plane.

What is the best way to do this?

• What if you fit a line? It would have low value where f is low, and high value where f is high. It would for a normal to the hyperplane of best separation. The search along that line would then be simpler than a search in the space. The domain is n-dimensional, but the range is 1d. Jul 13 '14 at 4:01
• Perhaps I am missing a key point. If you put your plane far away from the points, with all points on one side and no points on the other, then you could create an unbounded difference. Or do you also require that |V|/2 points are on one side and |V|/2 points are on the other? Which is certainly the more interesting problem. Feb 17 '19 at 16:14
• Numbers can be negative so your suggestion isn't correct. Feb 17 '19 at 18:07
• Do you have any information about $f$? Is continuous? Linear? Feb 19 '20 at 10:50
• $f$ is continuous but not linear. Feb 19 '20 at 12:44