A python package for prototype-based soft feature selection
Project description
sofes
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.
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.
pip install -U sofes
To install the development version from GitHub using Git, run the following command in your terminal:
pip install git+https://github.com/naotoo1/sofes
Bibtex
If you would like to cite the package, please use this:
@misc{Otoo_sofes_2023,
author = {Otoo, Nana Abeka},
title = {sofes},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished= {\url{https://github.com/naotoo1/sofes}},
}
Project details
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