Process of X-means cluster with text data

JoanneyuJoanneyu Member Posts: 13 Contributor I
edited November 2019 in Help
Hi all, 

I want to do x-means cluster with text data, but I am super new with Rapidminer. I followed several different tutorials and ended up with this process.
My data looks like the excel format at left hand side, where I have only one column with several single words.

If would be so nice if someone can confirm whether the process is right or wrong. I want to use X-means cluster because I want to see what is the ideal number of clusters. I am using TF-IDF, and Inside "process document from data", there are tokenize, transform cases, stopwords, and stem (poter). As for "X-Means", I set the k min of 10 and k max 60, with Cosine similarity. 

However, the results appear weird to me because cluster 0 has almost all the data. Also, I expected that the results will tell me what would be the most ideal number of clusters? Or did I make any mistake in the process?

Thank you in advance!!!


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    sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    hi @Joanneyu there's nothing that I can see wrong with your process (although I must say using Auto Model is MUCH easier than what you're trying to do here with operators). Having one cluster with almost all the items is not unusual per se; could be a very homogenous group, or you're not creating enough/the right features to find differences in your texts.
    Again I'd try Auto Model. :wink:
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