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Unsupervised clustering of categorical data

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Hi everyone,
I wanted to cluster a time serie dataset which has 30 timepoints and more than 50'000 rows. The dataset is categorical (from 1 to 6) which represent different categories.
The problem with my current clustergram method using the euclidian distance metrics, is that it will cluster the category 5 closer to 6. I don't want that, those categories are not somehow related. How is it possible to remove this bias in the clustering?
Hope my question is clear, thanks for your further help!
  2 Comments
Image Analyst
Image Analyst on 23 Nov 2021
Could be clearer if you attached a .mat file with your table, as many rows as will fit into 5 MB (attachment size limit).

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Answers (1)

Pratyush Roy
Pratyush Roy on 1 Dec 2021
Hi Daniel,
The link here might be helpful for clustering categorical or non-numeric data.
Hope this helps!

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