scikit-learn / scikit-learn/scikit-learn
sklearn.cluster.bicluster.BaseSpectral._svd: n_discard eigenvectors from svds
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Description
Description
The function sklearn.cluster.bicluster.BaseSpectral._svd incorrectly uses the parameters svd_method = 'arpack' and n_discard.
The function _svd should discard the eigenvectors with largest eigenvalues, but the function svds used when svd_method=='arpack' returns the eigenvectors with ascending eigenvalues. This behavior is different with that of the function randomized_svd used when svd_method=='randomized'.
Contributor guide
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Research direction
Start at sklearn.cluster.bicluster.BaseSpectral._svd and inspect how svd_method='arpack' calls svds versus how 'randomized' calls randomized_svd. Verify the eigenvector ordering and n_discard behavior for both methods; done means the arpack path discards the same intended eigenvectors as the randomized path.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100