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?
Andy
On 05/05/2016 11:16 PM, Johan Mazel wrote:
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 seems a bit off: either
underestimated or overestimated compared to dpcluster
(https://github.com/teodor-moldovan/dpcluster).
I wrote a small script that give two examples and attached it to this
mail.
Please tell me if I am doing anything wrong.
Thank you very much for your time.
Regards,
Johan
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