This is list of all the methods in unsupervised clustering methods:
https://scikit-learn.org/stable/modules/clustering.html
and out of these methods, following methods do not take custom pairwise distance matrix.
- BIRCH
- MeanShift
- KMeans
- MiniBatchKMeans
- WARD method (HCA)
I am looking for way(s) to have one of these methods (any of these methods) to take a parameter 'metric' and have it use a 'precomputed' distance matrix.
For example: for DBSCAN has a parameter 'metric' and that parameter takes a 'precomputed' distance matrix.
class sklearn.cluster.DBSCAN(eps=0.5, min_samples=5, metric='precomputed')
I am looking to implement the same as DBSCAN but for any of those above mentioned methods.
