| 6 | | * Don't know how to best unify covariance functions and kernel functions (there is some duplication). |
| 7 | | * The calculation of the covariance matrix takes a lot of time (10x longer than the equivalent calculation when using an equivalent covariance matrix). I suspect that the reason is the rather general implementation for distance calculation. |
| 8 | | * Beta should be a parameter of the algorithm instead of the kernel to make it easier to run a grid test. |
| | 6 | * Don't know how to best unify covariance functions and kernel functions (there is some duplication) (DONE). |
| | 7 | * The calculation of the covariance matrix takes a lot of time (10x longer than the equivalent calculation when using an equivalent covariance matrix). I suspect that the reason is the rather general implementation for distance calculation. (DONE) |
| | 8 | * Beta should be a parameter of the algorithm instead of the kernel to make it easier to run a grid test. (DONE) |
| | 9 | * Multiple of the implemented kernels are only conditionally positive definite. See http://num.math.uni-goettingen.de/schaback/teaching/sc.pdf for a definition of the kernels and valid beta-values. Additionally, it is necessary to extend the basis functions for these kernels depending on the value of beta. |
