Hi!
On Wed, Apr 27, 2016 at 2:46 PM, Li Aodong wrote:
>
> First, it is about the subsample parameter description. As the picture
> below, it says that "Choosing subsample < 1.0 leads to *a* *reduction of
> variance and an increase in bias*". But I think choosing subsample < 1.0
> actually* increa
Hi ,
After performing clustering, the cluster centers can be extracted via
.cluster_centers_.
A sample result is
kmeans.cluster_centers_
array([[ 1.01505989, -0.70632886],
[ 0.33475124, 0.89126382],
[-1.287003 , -0.43512572]])
How can *I interpret these values.*
*Can somebody he
Hi, Jaganadh,
it looks like you ran k-means on a 2-dimensional dataset (i.e., a dataset with
2 feature variables) and k=3. Thus, the results mean that these three cluster
centers (or “centroids”) are the centers of the 3 clusters that k-means
attempted to discover. Or in other words, there are
