The features are already in the distance passed to KMeans on creation.

Just keep track of the indices of the feature vectors that are selected as
cluster centres.
On 14 Jan 2014 11:21, "mazumdarparijat" <notifications@github.com> wrote:

> In src/shogun/clustering/KMeans.cpp:
>
> > @@ -454,6 +458,65 @@ void CKMeans::store_model_features()
> >  	SG_UNREF(rhs);
> >  }
> >
> > +SGMatrix<float64_t> CKMeans::kmeanspp()
> > +{
> > +	int32_t cent_id, mu_1, mu_next;
> > +	int32_t count=0;
> > +	float64_t dist_temp;
> > +	float64_t sum;
> > +
> > +	CDenseFeatures<float64_t>* muspp=new CDenseFeatures<float64_t>(0);
>
> Sir, I am actually trying to use the distance function to calculate
> distance. Please see line 487. I guess this will not be possible without
> creating features.
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/shogun-toolbox/shogun/pull/1814/files#r8855267>
> .
>