I try the understand how the Gaussian Process works. So if I'm sampling from it, I will get values, which come from a multivariate distribution.
Let's say I have 5 input features in my training data. So one training point is a 5d vektor like: [x1, x2, x3, x4, x5]. Each training point has a 1d target value.
After inferring the posterior distribution and plotting samples from the GP, what actually is on the y-axis and what is on the X-axis?
Am I right that the y-value, so actually the function value, is my target ? Is it right that on the x-axis there are indices, which stand for one training point, so here: [x1,x2,x3,x4,x5]?