There are many clustering algorithms in sklearn, we need to investigate which of these we can use for our application. Then we can also make a comparison of the quality of the flat clusterings produced by the different clustering algorithms. This is a lot of work because each clustering algorithms has different parameters that need to be tuned to our problem case to get good results.
There are many clustering algorithms in sklearn, we need to investigate which of these we can use for our application. Then we can also make a comparison of the quality of the flat clusterings produced by the different clustering algorithms. This is a lot of work because each clustering algorithms has different parameters that need to be tuned to our problem case to get good results.