Whitening parameter for PCA

[rasbt]

Description

Adds a whitening parameter to PrincipalComponentAnalysis, to optionally whiten the transformed data such that the features have unit variance.

Related issues or pull requests

Pull Request Checklist

• Added a note about the modification or contribution to the ./docs/sources/CHANGELOG.md file (if applicable)
• Added appropriate unit test functions in the ./mlxtend/*/tests directories (if applicable)
• Modify documentation in the corresponding Jupyter Notebook under mlxtend/docs/sources/ (if applicable)
• Ran nosetests ./mlxtend -sv and make sure that all unit tests pass (for small modifications, it might be sufficient to only run the specific test file, e.g., nosetests ./mlxtend/classifier/tests/test_stacking_cv_classifier.py -sv)
• Checked for style issues by running flake8 ./mlxtend

[pep8speaks]

Hello @rasbt! Thanks for updating the PR.

• There are no PEP8 issues in the file mlxtend/feature_extraction/principal_component_analysis.py !

• There are no PEP8 issues in the file mlxtend/feature_extraction/tests/test_principal_component_analysis.py !

Comment last updated on December 01, 2018 at 21:02 Hours UTC

[coveralls]

Coverage increased (+0.03%) to 91.829% when pulling 848d139 on pca-whitening into c9c949b on master.