Hi Johan.
Unfortunately there are known problems with DPGMM
https://github.com/scikit-learn/scikit-learn/issues/2454
There is a PR to reimplement:
https://github.com/scikit-learn/scikit-learn/pull/4802
I didn't know about dpcluster, it seems unmaintained. But maybe
something to compare against?
Hello
Sorry for the double post, I think there was a problem with my previous
message.
I am trying to use the DPGMM technique (
http://scikit-learn.org/stable/modules/generated/sklearn.mixture.DPGMM.html)
to find classes of data in 1-dimensional vectors.
The extracted variance/standard devaition
Hi
I am trying to use the DPGMM technique (
http://scikit-learn.org/stable/modules/generated/sklearn.mixture.DPGMM.html)
to find classes of data in 1-dimensional vectors.
The extracted variance/standard devaition seems a bit off: either
underestimated or overestimated compared to dpcluster (
https