Question

Many clustering algorithms that automatically determine the number of clusters claim that this is an advantage. List two situations in which this is not the case

Answer 1

The list of those two situations is given below.

Step-by-step explanation:

Case 1:

Yet another condition for manual cluster formation that wasn't an improvement would be whenever the number of observations measured is higher than even the machine can accommodate.

Case 2:

The second scenario which isn't an improvement whenever the original data is recognized for automated cluster analysis, and therefore also implementing the algorithms doesn't generate any extra details.