You are given a data set with 100 records and are asked to cluster the data. You

Question:

You are given a data set with 100 records and are asked to cluster the data. You use K means to cluster the data, but for all values of K, 1 ≤ K ≤ 100, the K-means algorithm returns only one non-empty cluster. You then apply an incremental version of K means, but obtain exactly the same result. How is this possible? How would single link or DBSCAN handle such data?