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Would it be possible to add a feature that allows one to embed an unseen/unlabeled data point to an existing embedding using metric learning? This would be similar to the function currently available with UMAP: https://umap-learn.readthedocs.io/en/latest/supervised.html
Thanks!
The text was updated successfully, but these errors were encountered:
If this could be implemented, it would be incredible. I absolutely love PaCMAP and have been using the dimensions as predictor variables for supervised models. This would take things to a new level
Thank you for your feedback! This feature is a top priority on our to-do list, and we are committed to working on it! We will keep you updated on our progress.
Would it be possible to add a feature that allows one to embed an unseen/unlabeled data point to an existing embedding using metric learning? This would be similar to the function currently available with UMAP:
https://umap-learn.readthedocs.io/en/latest/supervised.html
Thanks!
The text was updated successfully, but these errors were encountered: