Feature selection for Hard Voting classifier
Project description
binsel
Feature selection for Hard Voting classifier.
Usage
Check the `binsel_hardvote example <https://github.com/kmedian/binsel/blob/master/examples/binsel_hardvote.ipynb>`__ folder for notebooks.
Algorithm
The task is to select e.g. n_select=3 binary features from a pool of many binary features. These binary features might be the prediction of binary classifiers. The selected binary features are then combined into one hard-voting classifier.
A voting classifier should have the following properties
each voter (a binary feature) should be highly correlated to the target variable
the selected binary features should be uncorrelated.
The algorithm works as follows
Generate multiple correlation matrices by bootstrapping (see `korr.bootcorr <https://github.com/kmedian/korr/blob/master/korr/bootcorr.py>`__). This includes corr(X_i, X_j) as well as corr(Y, X_i) computation. Also store the oob samples for evaluation.
For each correlation matrix do …
Preselect the i* with the highest abs(corr(Y, X_i)) estimates (e.g. pick the n_pre=? highest absolute correlations)
Slice a correlation matrix corr(X_i*, X_j*) and find the least correlated combination of n_select=? features. (see `korr.mincorr <https://github.com/kmedian/korr/blob/master/korr/mincorr.py>`__)
Compute the out-of-bag (OOB) performance (see step 1) of the hard-voter with the selected n_select=? binary features
Select the binary feature combination with the best OOB performance as final model.
Appendix
Installation
The binsel git repo is available as PyPi package
pip install binsel
Install a virtual environment
python3.7 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
pip install -r requirements-dev.txt
pip install -r requirements-demo.txt
(If your git repo is stored in a folder with whitespaces, then don’t use the subfolder .venv. Use an absolute path without whitespaces.)
Python commands
Jupyter for the examples: jupyter lab
Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')
Run Unit Tests: python -W ignore -m unittest discover
Publish
pandoc README.md --from markdown --to rst -s -o README.rst
python setup.py sdist
twine upload -r pypi dist/*
Clean up
find . -type f -name "*.pyc" | xargs rm find . -type d -name "__pycache__" | xargs rm -r rm -r .venv
Support
Please open an issue for support.
Contributing
Please contribute using Github Flow. Create a branch, add commits, and open a pull request.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.