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 Kommentare
Image Analyst
am 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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