We will try to map a complex (strongly non-linear) function with as few a samples as possible.

We will use the Styblinski–Tang function defined as

\begin{align} f([x_1...x_n]) = \sum_{i=1}^n \frac{x_i^4 - 16 x_i^22 + 5 x_i}{2} \end{align}

And we will work with 2 variables.

In order to map that function, we will combine two tools : an efficient latin hypercube sampler and a support vector regression with a gaussian kernel trick.