LinNgua
Technical User
- Dec 31, 2013
- 1
Hi everyone and happy new year!
I have to analyse a data set with weka clustering, using 3 clustering algorithms and I need to provide a comparison between them about their performance and suitability. The comparison may include a description about how to adjust parameter values of the clustering algorithms to make them perform better. The three algorithms are SimpleKmeans, DBSCAN and HierarchicalClusterer.
So, my questions are: What kind of variables do I need to look at when measuring performance and suitability? The one that I managed to find so far is Within cluster sum of squared errors. And also, which parameter values do I need to adjust in order to make the algorithms perform better?
Thanks!
I have to analyse a data set with weka clustering, using 3 clustering algorithms and I need to provide a comparison between them about their performance and suitability. The comparison may include a description about how to adjust parameter values of the clustering algorithms to make them perform better. The three algorithms are SimpleKmeans, DBSCAN and HierarchicalClusterer.
So, my questions are: What kind of variables do I need to look at when measuring performance and suitability? The one that I managed to find so far is Within cluster sum of squared errors. And also, which parameter values do I need to adjust in order to make the algorithms perform better?
Thanks!