I am trying to analyse a dataframe using hierarchical clustering hclust function in R. I want to test a large number of plausible distance metrics along with the full set of clustering methods. So far using expand.grid I have got
hyperparams = expand.grid(Meths=c("ward.D","ward.D2","single","complete","average","mcquitty","median","centroid"), Dists=c("euclidean", "maximum", "manhattan", "canberra", "binary","minkowski"))
The problem is that the dist function that is passed to hclust, when used with minkowski distance specifically, takes a further parameter p. For example, with iris, you could perform the HCA yourself using Minkowski distance with p=3/2 for example, with:
contingtab = table(iris$Species, cutree(hclust(dist(iris[,1:4],method="minkowski",p=3/2),method="complete"),3))
I get an error if I try to simply include "minkowski, p=3/2" in my list for Dists... however, if the method is anything but "minkowski", no p parameter is to be included.
I would like to pass in a vector of p values I'll write beforehand (maybe something like c(5/4, 3/2, 7/4, 9/4)) and be able to have these specified as the different p value options with Minkowski distance when I use expand.grid. Ideally, when hyperparams is viewed, it would also be clear which value of p has been used for each minkowski, i.e. they should be labelled. So for example, where (if you run my code for hyperparams) there would currently just be one minkowski under Dists, for each of the methods in Meths, there would be, if I supplied the p vector as c(5/4, 3/2, 7/4, 9/4), now instead 4 rows for Minkowski distance: minkowski, p=5/4, minkowski, p=3/2, minkowski, p=7/4, minkowski, p=9/4 (or looking something like that, making the p values clear). Any ideas?
（注意：请不要提供任何软件包，只能以R为基数！）
