I have a very basic question on clustering. After I have found k clusters with their centroids, how do I go about interpreting the classes of the data points that I have clustered (assigning meaningful class labels to each cluster). I am not talking about validation of the clusters found.
Can it be done given a small labelled set of data points, compute to which cluster these labelled points belong to and based on type and number of points each cluster receives, decide the label? This seems pretty obvious but I don't know how standard it is to assigns labels to clusters this way.
To be clear, I want to perform unsupervised clustering that doesn't use any labels to first find my clusters. Then having found the clusters, I want to assign meaningful class labels to the clusters based on the properties of a few example datapoints.