"Dynamically determine number of clusters k-means"

Answers

• Options

  awchisholm RapidMiner Certified Expert, Member Posts: 458 Unicorn

  October 2013

  Hello
  
  It is possible to convert a log to an example set; use the Log to Data operator. For Davies-Bouldin, you could look for a minimum by sorting this example set by the validity measure and then simply using the value of k that is associated with it.
  
  If you are confident that the data is well behaved in all cases then you could try that.
  
  Regards
  
  Andrew

  0
• Options

  Farnoush_r Member Posts: 5 Contributor II

  October 2013

  Thank you for your helpful response but i have two more questions. First, I followed your proposition I have an example set which determines the best number of clusters, but is it possible to enter this to a clustering node and the clustering node read the number of clusters from the data? I thin the k should be set in the clustering node and it does not read it from an outer source
  
  Second, I did not understand your worry about my data, cause apparently I am determining k each time based on the imported data and with any data the process determines the best k. so what is the problem?

  0
• Options

  awchisholm RapidMiner Certified Expert, Member Posts: 458 Unicorn

  October 2013

  For the first question, use the Extract Macro operator to get the data value of a particular attribute and example within an example set. Use that macro later however you want.
  
  For the second question, the Davies Bouldin validity measure uses mathematics to create a measure to identify clusters that are  relatively less scattered individually and are maximally separated from one another. Who is to say whether this mathematical algorithm matches what truly is the best clustering?
  

  0