[ML] Some corrections to ANOVA for Bayesian Optimisation

[tveasey]

This corrects the handling of the shifting and scaling of the function values when computing various quantities related to the GP. In particular, we were not properly undoing the transform in evaluate, evaluate1D and various ANOVA related functionality. We could end up computing square roots of negative numbers in evaluate1D and anovaTotalVariance. At the same time I took the opportunity to ensure GP domain is [0, 1]^n rather than just scaling. This leads to more predictable numerics for ML and also simplifies the code.

I've added tests that the kernel parameters are invariant under operations to the function range which should preserve its value: changing level and scale. I also do the same for evaluate, evaluate1D and various ANOVA related functionality.

[valeriy42]

Good work on catching the numerical issue and writing unit tests to verify the correct behaviour! 🚀