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"how to evaluate and compare two clustering method including k-mean"
Hi
I want to apply two clustering method including k-mean to my data and then compare them. Is there any way in rapidminer for copmaring clustering ?
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Answers
Hi Soehill,
Yes, that's quite easy to do. You would just need a Multiply operator after your data set and then connect the different clustering algorithms to it. Make sure to then output all the Clustering algo ports. Of course, you can use a Write CSV operator to write out the results too.
Something like this perhaps?
Tnx but I hadn't any problem with applying algorithms. Actually I apply K-Mean, K-Medoid and DBScan and I saved the results. Now I want to compare these results with each other and I don't know which operator should I use !
I had found "cluster distance performance", "cluster density performance " and "item distribution performance". Which one is suitable for comparing K-Mean, K-Medoid and DBScan ?
Can I use Davies Bouldin ?
Two performance measures are supported by 'Cluster Distance Performance':
Average within cluster distance and
Davies-Bouldin index
.
And a quick help: You can use performance to data to make a example set from your performance vector. Afterwards it's easy to compare values with standard ETL tools.
~Martin
Dortmund, Germany