> Thanks for the explanations. But what am seeing is that if I feed a data with
> 3K features/attributes the "cluster_centers_ method will give 3K values for
> each clusters.
Yes, that’s correct!
> My objective is to give a name to each cluster based on the feature names
> closest to the cent
Hi Sebastian,
Thanks for the explanations. But what am seeing is that if I feed a data
with 3K features/attributes the "cluster_centers_ method will give 3K
values for each clusters. My objective is to give a name to each cluster
based on the feature names closest to the centroids .
Best
Jagan
O
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
