Metadata-Version: 2.1
Name: sofes
Version: 0.0.1
Summary: A python package for prototype-based soft feature selection
Home-page: https://github.com/naotoo1/sofes
Author: Nana Abeka Otoo
Author-email: abekaotoo@gmail.com
License: MIT license
Keywords: sofes
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dataclasses==0.6
Requires-Dist: imbalanced-learn==0.8.1
Requires-Dist: imblearn==0.0
Requires-Dist: matplotlib==2.0.0
Requires-Dist: numpy
Requires-Dist: pandas==0.24.0
Requires-Dist: scikit-learn==0.24.2
Requires-Dist: scipy==1.5.4
Requires-Dist: sklearn-lvq==1.1.1

# sofes


[![image](https://img.shields.io/pypi/v/sofes.svg)](https://pypi.python.org/pypi/sofes)
[![python: 3.60](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-3610/)
[![github](https://img.shields.io/badge/version-0.0.1-yellow.svg)](https://github.com/naotoo1/sofes)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

**A python package for prototype-based feature selection**

Sofes is a prototype-based soft feature selection package wrapped around the
highly interpretable Matrix Robust Soft Learning Vector Quantization (MRSLVQ) and the Local
MRSLVQ algorithms. The process of assessing feature relevance with Sofes aligns with a comparable
approach established in the nafes package, with the primary distinction being the utilization of
prototype-based induction learners influenced by a probabilistic framework.

    

## Installation
sofes can be installed using pip.
```python
pip install sofes
```

If you have installed Prosemble before and want to upgrade to the latest version, you can run the following command in your terminal:
Prosemble can be installed using pip.
```python
pip install -U sofes
```


To install the development version from GitHub using Git, run the following command in your terminal:
```python
pip install git+https://github.com/naotoo1/sofes
```


## Bibtex
If you would like to cite the package, please use this:
```python
@misc{Otoo_sofes_2023,
author = {Otoo, Nana Abeka},
title = {sofes},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished= {\url{https://github.com/naotoo1/sofes}},
}
```


