Magnitude issue about gmr HOT 9 CLOSED

I did not fully understand it yet. Maybe it's numerical problem (for example, exp(small value) -> 0 or exp(large value) -> infinity). If you are interested and want to help you can take a look. I would be happy about any support.

from gmr.

No problem. I would appreciate any feedback before I merge it.

from gmr.

Hi,

this is an issue that seems to be a bit difficult to fix on the algorithm's side. I would recommend to use sklearn.preprocessing.StandardScaler on your data if this is an issue.

from gmr.

All right, by curiosity what is causing this issue?

from gmr.

OK, most likely the covariances have to be initialized differently. Means are already initialized to data points but the covariances are always identity matrices. Their variance should be set to something like (average distance / number of Gaussians) ** 2. I don't know if that will fix it though.

from gmr.

Great, I'll try to have a deeper look at it next weekend.
It also seems like the Gaussians do not fit the data the same way as GMM goes it in the sklearn package.

from gmr.

@Labulitiolle Did you have a chance to look into the issue? Meanwhile I also tried some things. See #10

from gmr.

Hi @AlexanderFabisch ,
I am really sorry, it's been a bit of a rush lately. Your commit seems to bring great improvement.
It is still on my todo list to go through the code. I can't give you a fixed date though...

from gmr.

Thanks. I merged it just a few seconds ago.

from gmr.