Generic feature selector with categorical features and pd.DataFrame support #1

jonathan-taylor · 2021-10-05T04:40:16Z

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 PYTHONPATH='.' pytest ./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., PYTHONPATH='.' pytest ./mlxtend/classifier/tests/test_stacking_cv_classifier.py -sv)
Checked for style issues by running flake8 ./mlxtend

…uential as special cases; allows for categorical variables

jonathan-taylor added 4 commits October 4, 2021 20:53

WIP: generic feature selector added; includes both exhaustive and seq…

425348a

…uential as special cases; allows for categorical variables

using a named tuple to describe the search strategy

4c76af3

utilities for extracting columns from a matrix or dataframe

2b174cb

reverting exhaustive to previous version

bf42afa

jonathan-taylor changed the title ~~Categorical features~~ Generic feature selector with categorical features and pd.DataFrame support Oct 5, 2021

jonathan-taylor merged commit 0d236f9 into master Oct 5, 2021

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