Overfitting in an unsupervised technique I am trying to understand if over-fitting can happen in an unsupervised technique like kmeans clustering. Could someone help me understand if and how this would happen?

Thanks.
I'm not sure if this is valid but how about two trivial clustering examples:


Every object belongs to cluster which contain only this object. So for example if you would like to cluster N cars, there will be N clusters - one for each car.
On the other hand there could be case when algorithm will pick one cluster which will contain all elements inside it - one cluster with all N cars.


Those will be valid clusters but obviously they will not give you any useful information.