Comments (1)
Hi,
Great question. Unfortunately in its current iteration, UMAP isn't parametric and thus cannot do out of sample transformation. You currently have to run fit_transform
on the entire dataset rather than fit
.
The current version of UMAP implements ParametricUMAP
which can do out of sample prediction, and also allows you to use densMAP parameters, so you can do density preserving parametric UMAP.
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Related Issues (12)
- where is requirements.txt HOT 2
- Integration with UMAP repository HOT 2
- Error in py_call_impl(callable, dots$args, dots$keywords) : ValueError: Buffer has wrong number of dimensions (expected 1, got 2) HOT 7
- Distribution as R package HOT 6
- How can I get the cluster information of cells after densvis processing? HOT 1
- ZeroDivisionError: division by zero HOT 2
- Can densMAP (in development version of Seurat) yield reproducible clustering? HOT 3
- How to find the quantitative evaluation of density preservation? HOT 2
- Can I know the simulation settings? HOT 2
- Support for Numba 0..55.2
- Install issue on apple silicon
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