Solved – Clustering of set of matrices

clusteringmatrix

I have 25 matrices 19×19 containing coherence measure between EEG electrodes. I want to divided them into some groups by clustering or any other method. I know how to deal with vectors, but I can't find anything about clustering of set of matrices. If it can help – I think we can use coherence as a distance between cells into matrix. So may be there are some method for clustering of distance matrices?

EDIT

Traditional clustering methods cluster vectors. In the vector space, the distance metric
and other distance functions are well defined. The Euclidean distance between vectors
$x_1$ and $x_2$ is $|x_1-x_2|_2$, the 2-norm of $x_1-x_2$. Analogously, to compare two matrices $M_1$ and $M_2$, we may want to compute $|| M_1-M_2||_p$, the p-norm of $M_1-M_2$.

EDIT

While there are two solution:

  1. Compute distance between matrices as sum of squares of the difference matrix
  2. Unwrap a triangle of each matrix into a vector

Is there something else?

Best Answer

Since you have only 25 instances, I think hierarchical clustering is the way to go.

Not much more to say, until you've tried it - it's straightforward to use with any similarity, and with 25 instances, the bad scalability of O(n^3) is also irrelevant.

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