Inline.

Bert Gunter


On Sun, Apr 14, 2019 at 4:12 PM Leszek Nowina <leekoi...@gmail.com> wrote:

>     > asdf = data.frame(x=c(1,2,3), y=c(4,5,6), z=c(7,8,9))
>     > cutree(agnes(asdf), h=100)
>     Error in cutree(agnes(asdf), h = 100) :
>       the 'height' component of 'tree' is not sorted (increasingly)
>     > cutree(diana(asdf), h=100)
>     Error in cutree(diana(asdf), h = 100) :
>       the 'height' component of 'tree' is not sorted (increasingly)
>
> I'm not sure if I understand why this is the case.
>
> This is what I want: Cluster stuff by the //distances//, **not** by
> how many clusters I want to have.
>
> If two things are further from each other than X, they should go to
> different clusters. Otherwise, the same cluster.
>
> Is it unreasonable what I'm asking for?

Yes.

X and Y are at a distance 2. Y and Z are at a distance 2. X and Z are at a
distance 4. Your idea cannot be consistently applied if 3 is the cutoff for
clustering: Xand Z would have to go in different clusters but both be in
the same cluster as Y.

Maybe you need to spend some time with the literature before trying to cook
up your own notions.

Cheers,
Bert



> I image if I was to manually
> implement Agnes or Diana this would go like that: stop joining
> clusters if the smallest distance between any pair of clusters is
> larger than X (Agnes) or stop dividing clusters if the largest cluster
> has a diameter of X (Diana); but since both methods always join/divide
> to the very end I thought using cutree with a height parameter would
> give me what I need. It won't.
>
> Am I missing something?
>
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