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I am trying to cluster sparse heterogeneous datasets containing demographics and diagnosis variables ( mix of categorical and numerical variables). How should I start my clustering endeavors ? start with dimensionality reduction methods such as Factor analysis of mixed data (FAMD) to handle sparsity then performing clustering ? Or instead start directly with clustering methods using Gower’s distance?

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  • $\begingroup$ Please accept answers to your many questions across the various StackExchange sites. You are starting to look very selfish, and I'm sure you wouldn't want that $\endgroup$
    – roaima
    Apr 16 at 6:27

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