REF: hack to be able to share distutils utilities.#1
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amueller merged 1 commit intoamueller:linking_arrayfuncsfrom Jul 25, 2012
Merged
REF: hack to be able to share distutils utilities.#1amueller merged 1 commit intoamueller:linking_arrayfuncsfrom
amueller merged 1 commit intoamueller:linking_arrayfuncsfrom
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We took the ugly trick from NumPy to separate build vs normal use of sklearn imports.
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REF: hack to be able to share distutils utilities.
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Thanks, sweet :) |
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…scikit-learn#7838) * initial commit for return_std * initial commit for return_std * adding tests, examples, ARD predict_std * adding tests, examples, ARD predict_std * a smidge more documentation * a smidge more documentation * Missed a few PEP8 issues * Changing predict_std to return_std #1 * Changing predict_std to return_std #2 * Changing predict_std to return_std #3 * Changing predict_std to return_std final * adding better plots via polynomial regression * trying to fix flake error * fix to ARD plotting issue * fixing some flakes * Two blank lines part 1 * Two blank lines part 2 * More newlines! * Even more newlines * adding info to the doc string for the two plot files * Rephrasing "polynomial" for Bayesian Ridge Regression * Updating "polynomia" for ARD * Adding more formal references * Another asked-for improvement to doc string. * Fixing flake8 errors * Cleaning up the tests a smidge. * A few more flakes * requested fixes from Andy * Mini bug fix * Final pep8 fix * pep8 fix round 2 * Fix beta_ to alpha_ in the comments
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Jul 17, 2018
* Add averaging option to AMI and NMI Leave current behavior unchanged * Flake8 fixes * Incorporate tests of means for AMI and NMI * Add note about `average_method` in NMI * Update docs from AMI, NMI changes (#1) * Correct the NMI and AMI descriptions in docs * Update docstrings due to averaging changes - V-measure - Homogeneity - Completeness - NMI - AMI * Update documentation and remove nose tests (#2) * Update v0.20.rst * Update test_supervised.py * Update clustering.rst * Fix multiple spaces after operator * Rename all arguments * No more arbitrary values! * Improve handling of floating-point imprecision * Clearly state when the change occurs * Update AMI/NMI docs * Update v0.20.rst * Catch FutureWarnings in AMI and NMI
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We took the ugly trick from NumPy to separate build vs normal use of
sklearn imports.