I'm implementing a clustering model, and it uses exp(-d) as a neighbourhood func tion, where d is index denoting order by distance. The idea is, if d is 0, you get 1, and as d increases its influence decreases fast, so it can be used to se lect neighbourhoods.
This works when, in d, 0 means closest and biggest one means farthest; however, problem is, I have to use indexes that are semantically inverse: 0 means farthe st, while biggest means closest. What can I use, instead of exp(-d), that would have similar neighbourhood-type outputs?