This is a python implementation of the CMFS algorithm for feature selection (paper included in the repository). Currently the implementation has only been completed on a toy dataset.
TODO:
- Implement this algorithm on 22NG dataset.
- Perform benchmark testing against Chi-square, IG feature selection algos on same dataset.
To contribute:
- Fork this repo.
- Clone your forked repo via
git clone <repo URL>
. - Create new branch via
git checkout -b branch-name
. - Stage files via
git add file-name
. - Commit via
git commit -m "message"
. - Push via
git push -u origin branch-name
.
Current Dependencies:
- Gensim
- Numpy
- Run the notebook via Jupyter notebook