- Compute the Distance Matrix: If you haven't already, compute the pairwise distance matrix for your data vector V. This matrix should be a square, symmetric matrix where the element at position (i, j) represents the distance between the ith and jth elements of V.
- Convert the Distance Matrix to a Vector: The linkage function requires the distance matrix to be in vector form, as returned by the pdist function.
- Perform Hierarchical Clustering: Use the linkage function with your custom distance vector. You can specify the linkage method (e.g., 'single', 'complete', 'average').
- Form Clusters: Use the cluster function to form clusters from the hierarchical tree.
Cluster with custom metric
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Hi
I want to cluster my data using a custom distance metric, so I have some data vector V and a matrix with distances between the rows of V, pairwise. How to do it? I saw that linkage might solve it but I have no idea how to pass my metric there
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Answers (1)
arushi
on 22 Aug 2024 at 9:52
Hi Teresa,
To cluster your data using a custom distance metric in MATLAB, you can use the linkage function, which supports clustering based on a precomputed distance matrix. If you already have a matrix of pairwise distances, you can pass it directly to the linkage function.
Steps to Cluster Using a Custom Distance Matrix
Hope this helps.
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