https://github.com/ctlab/ITMO_FS
Feature selection library in python
https://github.com/ctlab/ITMO_FS
feature-selection machine-learning
Last synced: about 1 year ago
JSON representation
Feature selection library in python
- Host: GitHub
- URL: https://github.com/ctlab/ITMO_FS
- Owner: ctlab
- License: bsd-3-clause
- Created: 2020-02-26T08:13:44.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-02-22T20:02:16.000Z (over 3 years ago)
- Last Synced: 2025-04-16T04:21:20.346Z (about 1 year ago)
- Topics: feature-selection, machine-learning
- Language: Python
- Homepage:
- Size: 72.7 MB
- Stars: 146
- Watchers: 9
- Forks: 38
- Open Issues: 12
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
.. -*- mode: rst -*-
.. image:: docs/logos/logo_itmo_fs_itog_colour.jpg
:scale: 10 %
:target: https://en.itmo.ru/
ITMO_FS
=======
Feature selection library in Python
Package information: |Python 2.7| |Python 3.6| |License| |Docs| |CodeCov|
Install with
::
pip install ITMO_FS
Current available algorithms:
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Supervised filters | Unsupervised filters | Wrappers | Hybrid | Embedded | Ensembles |
+==============================================+===============================================+==============================+=================+==========+=================+
| Spearman correlation | Trace Ratio (Laplacian) | Add Del | Filter Wrapper | MOSNS | MeLiF |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Pearson correlation | Multi-Cluster Feature Selection | Backward selection | IWSSr-SFLA | MOSS | Best goes first |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Fit Criterion | Unsupervised Discriminative Feature Selection | Sequential Forward Selection | | RFE | Best sum |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| F ratio | | QPFS | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Gini index | | Hill climbing | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Symmetric Uncertainty | | Simulated Annealing | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Fechner correlation | | Recursive Elimination | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Kendall correlation | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Information Gain | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| ANOVA | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Chi-squared | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Relief | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| ReliefF | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Laplacian score | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Modified T-score | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Mutual Information Maximization | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Minimum Redundancy Maximum Relevance | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Joint Mutual Information | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Conditional Infomax Feature Extraction | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Mutual Information Feature Selection | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Conditional Mutual Info Maximization | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Interaction Capping | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Dynamic Change of Selected Feature | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Composition of Feature Relevancy | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Max-Relevance and Max-Independence | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Interaction Weight | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Double Input Symmetric Relevance | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Fast Correlation | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Statistical Inference Relief | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Trace Ratio (Fisher) | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Nonnegative Discriminative Feature Selection | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Robust Feature Selection | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| Spectral Feature Selection | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| VDM | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| QPFS | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
| MIMAGA | | | | | |
+----------------------------------------------+-----------------------------------------------+------------------------------+-----------------+----------+-----------------+
Documentation:
https://itmo-fs.readthedocs.io/en/latest/
.. |Python 2.7| image:: https://img.shields.io/badge/python-2.7-blue.svg
.. |Python 3.6| image:: https://img.shields.io/badge/python-3.6-blue.svg
.. |License| image:: https://img.shields.io/badge/license-BSD%20License-blue.svg
.. |Docs| image:: https://readthedocs.org/projects/itmo-fs/badge/?version=latest
.. |CodeCov| image:: https://codecov.io/gh/ctlab/ITMO_FS/branch/master/graph/badge.svg
:target: https://codecov.io/gh/ctlab/ITMO_FS