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Package Details: python-yellowbrick 1.5-1

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Git Clone URL:	https://aur.archlinux.org/python-yellowbrick.git (read-only, click to copy)
Package Base:	python-yellowbrick
Description:	A suite of visual analysis and diagnostic tools for machine learning
Upstream URL:	https://github.com/DistrictDataLabs/yellowbrick
Licenses:	Apache
Submitter:	hexd
Maintainer:	hexd
Last Packager:	hexd
Votes:	0
Popularity:	0.000000
First Submitted:	2018-08-30 22:03 (UTC)
Last Updated:	2023-07-15 20:59 (UTC)

Dependencies (14)

python-cycler
python-matplotlib (python-matplotlib-git^AUR)
python-numpy (python-numpy-flame^AUR, python-numpy-mkl-bin^AUR, python-numpy-git^AUR, python-numpy1^AUR, python-numpy-mkl^AUR, python-numpy-mkl-tbb^AUR)
python-scikit-learn (python-scikit-learn-git^AUR)
python-scipy (python-scipy-mkl-bin^AUR, python-scipy-git^AUR, python-scipy-mkl^AUR, python-scipy-mkl-tbb^AUR)
python-setuptools (make)
python-pytest (check)
python-pytest-cov (check)
python-pytest-flakes^AUR (check)
nltk-data (optional) – Alternative to download the corpora/treebank for NLTK
python-nltk (optional) – NLTK as the PosTagVisualizer/postag parser
python-pandas (optional) – Datasets as pandas.DataFrame instead of numpy arrays
python-spacy^AUR (python-spacy-git^AUR) (optional) – SpaCy as the PosTagVisualizer/postag parser
python-umap-learn^AUR (optional) – UMAP Corpus Visualization with UMAPVisualizer/umap

Required by (0)

Sources (1)

yellowbrick-1.5.tar.gz

Latest Comments

hexd commented on 2023-07-15 21:03 (UTC)

This one was quite difficult to let tests pass in v1.5-1.

As of now, it seems the library is relying on old APIs of old versions of the requirements (e.g. there are many deprecation warnings from matplotlib), which is okay while it's still compatible with the recent libs, but that's unfortunately not the case everywhere. I wasn't able to make DispersionPlot work (I would need to dig further in yellowbrick's code and this would go beyond packaging needs), but for all the rest, it should be working.

I applied a small patch to make yellowbrick.cluster.elbow.distortion_score work with sparse 2D arrays. It used to work with sparse matrices, but these are no longer accepted by the upstream lib. All other patches are only for testing.