You can just set `means_` and `covars_` attributes before fitting. But GMM
will also run the KMeans hotstarting for you if you like. e.g. if you don't
have a `means_` attribute and have and `m` in `init_params`, it runs kmeans
before fitting as shown on this line of the source code:
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/mixture/gmm.py#L436
-Robert
On Mon, Mar 24, 2014 at 4:39 AM, Yogesh Karpate <[email protected]>wrote:
> Hi ,
> I want to use GMM from sklearn for my application. Since
> Gmm is sensitive to initial parameters, I derive initial
> parameters from running K means on the data and
> subsequently feed them to GMM.
>
> How can I feed these parameters in GMM class of sklearn?
> *params* ,
> *init_params??*
>
> --
> Warm Regards
> Yogesh Karpate
>
>
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