Welcome to MAFESE’s documentation!¶
MAFESE (Metaheuristic Algorithms for FEature SElection) is the largest python library focused on feature selection using meta-heuristic algorithms.
Free software: GNU General Public License (GPL) V3 license
Total Wrapper-based (Metaheuristic Algorithms): > 200 methods
Total Filter-based (Statistical-based): > 15 methods
Total Embedded-based (Tree and Lasso): > 10 methods
Total Unsupervised-based: >= 4 methods
Total datasets: >= 30 (47 classifications and 7 regressions)
Total performance metrics: >= 61 (45 regressions and 16 classifications)
Total objective functions (as fitness functions): >= 61 (45 regressions and 16 classifications)
Documentation: https://mafese.readthedocs.io/en/latest/
Python versions: >= 3.7.x
Dependencies: numpy, scipy, scikit-learn, pandas, mealpy, permetrics, plotly, kaleido
Features¶
- Our library provides all state-of-the-art feature selection methods:
Filter-based FS
- Embedded-based FS
Regularization (Lasso-based)
Tree-based methods
- Wrapper-based FS
Sequential-based: forward and backward
Recursive-based
MHA-based: Metaheuristic Algorithms
Unsupervised-based FS
We have implemented all feature selection methods based on scipy, scikit-learn and numpy to increase the speed of the algorithms.
Quick Start:
Models API:
Support: