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kmeans works with some values of k and not works with other
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Peter Perkins on 12 Dec 2014
If f1 is a binary matrix, then it certainly does make sense to cluster your data into more than two clusters. Each column of f1 is treated as an N-D binary vector, and (if n were 3, for example), one cluster might be [0;0;1], another [0;1;0], and the third [1;0;0]. This isn't very interesting in 3D, but in higher dimensions. it might well be.
You are clustering binary data using (squared) Euclidean distance. There are other choices for the distance function that are likely more appropriate, read the doc.
The empty cluster error is simply because (apparently) your data do NOT contain more than two clusters and KMEANS is having trouble figuring out what to put in a third one. There is a parameter to KMEANS that controls how to handle this, again, read the doc.
Hope this helps.