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I am have a data set with 52 variables. Most of them have zeros, it resembles a sparse matrix. How can I cluster this kind of data and are there any special types of clustering? I am attaching pca plot

enter image description here

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It doesn't require any special method. The algorithm of choice depends on your data if for instance Euclidean distance works for your data or not.

Generally, you can try Kmeans or other methods on your X or PCAs; but Hierarchical Clustering may be a good choice for visualizing the clusters for high dimensional data.

enter image description here

Please check here if you can read/write python code.

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  • $\begingroup$ I guess the problem of the poster that it is a high dimensional sparse data. Traditional distance metrics will not work well in this case. $\endgroup$ – Viktor Jan 15 at 11:26

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