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Semi-related to #4 , but my case is that I want to use HUMAP on a supervised data where I have a training data with labels, and I want to be able to project new test data with the same embeddings. UMAP supports this use case, I was wondering if this would be theoretically possible with HUMAP as well? Would be nice to be able to use HUMAP to interpret classifier decisions.
The text was updated successfully, but these errors were encountered:
@stallam-unb I think it's possible. My question would be: where transforming on different hierarchical levels benefit more than transforming after projecting the whole dataset?
Semi-related to #4 , but my case is that I want to use HUMAP on a supervised data where I have a training data with labels, and I want to be able to project new test data with the same embeddings. UMAP supports this use case, I was wondering if this would be theoretically possible with HUMAP as well? Would be nice to be able to use HUMAP to interpret classifier decisions.
The text was updated successfully, but these errors were encountered: