Should mixture models have a clusterer-compatible interface #10336
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In my opinion, yes. I wanted to compare K-Means, GMM and HDBSCAN and was very disappointed that GMM does not have a |
I think we should add |
I would like to work on this! |
@Eight1911 go for it. It is probably relatively simple but maybe not entirely trivial. |
@Eight1911 Mind if I take a look at this? |
@Eight1911 Do you mind if I jump in as well? |
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Mixture models are currently a bit different. They are basically clusterers, except they are probabilistic, and are applied to inductive problems unlike many clusterers. But they are unlike clusterers in API:
n_components
parameter, with identical purpose ton_clusters
labels_
of the training datafit_predict
methodAnd they are almost entirely documented separately.
Should we make the MMs more like clusterers?
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