Comments (3)
For the above example, the problem disappears when changing the embedding parameters:
That can't be right, can it?
embedding = umap.UMAP(
n_components=20,
metric='correlation'
).fit_transform(digits.data)
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This is a bug in the code where a constant embedding dimension of two got left in somewhere. I'll fix that and the csgraph issue (which is apparently scipy 1.0 related) and try to get a bug fix release out tonight. Thanks for the report!
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Fixed in aace7a2. Closing.
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Related Issues (20)
- What is the best way to regularize supervised UMAP? HOT 1
- Parametric UMAP saves multiple copies of full input data HOT 2
- Cluster clusters
- argument n_training_epochs in ParametricUMAP is no longer supported but it is referred in the Documentation HOT 1
- serializing umap crashes application because of exploding memory HOT 2
- Embedding is non-reproducible between windows 11 machine and ubuntu 22 HOT 2
- Fatal Python error: Fatal Python error: Segmentation faultSegmentation fault
- Segmentation Fault (Error 139) When Running UMAP Transform
- Problem in supervised multilabel reduction, "truth value of an array is ambiguous"
- UMAP and HDBSCAN on 7.5 million Dataset HOT 11
- Pickle issue with load_ParametricUMAP HOT 3
- Umap with NumPy 2.0.0 fails due to return_inverse in unique
- More granular editor access. Multiple groups and per layer assignment
- Why are the ticks of the plot disabled? HOT 3
- Higher Loss Values in Parametric UMAP Notebooks HOT 2
- 0.5.6 is not available for macos HOT 2
- Add georeferenced tiff image ad layer
- Recommendations on densMAP vs. UMAP
- Parametric UMAP unknown shape error when fit on large datasets
- output umap clusters (label, features and cluster id) HOT 1
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