mulearn

A python package for inducing membership functions from labeled data

mulearn is a python package implementing the metodology for data-driven induction of fuzzy sets described in

D. Malchiodi and W. Pedrycz, Learning Membership Functions for Fuzzy Sets through Modified Support Vector Clustering, in F. Masulli, G. Pasi e R. Yager (Eds.), Fuzzy Logic and Applications. 10th International Workshop, WILF 2013, Genoa, Italy, November 19–22, 2013. Proceedings., Vol. 8256, Springer International Publishing, Switzerland, Lecture Notes on Artificial Intelligence, 2013;
D. Malchiodi and A. G. B. Tettamanzi, Predicting the Possibilistic Score of OWL Axioms through Modified Support Vector Clustering, in H. Haddad, R. L. Wainwright e R. Chbeir (Eds.), SAC'18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing, ACM (ISBN 9781450351911), 1984–1991, 2018.

Install

The package can easily be installed:

Name		Name	Last commit message	Last commit date
Latest commit History 32 Commits
docs		docs
mulearn		mulearn
tests		tests
v0.1.8		v0.1.8
.gitignore		.gitignore
.readthedocs.yml		.readthedocs.yml
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
README.md		README.md
environment.yml		environment.yml
environment_rtd.yml		environment_rtd.yml
ieee-paper-results.ipynb		ieee-paper-results.ipynb
lagrange-mulearn-doc.ipynb		lagrange-mulearn-doc.ipynb
lagrange-mulearn.ipynb		lagrange-mulearn.ipynb
main.py		main.py
mulearn-compare.py		mulearn-compare.py
mulearn-documentation.ipynb		mulearn-documentation.ipynb
mulearn-unsupervised.ipynb		mulearn-unsupervised.ipynb
settings.ini		settings.ini
setup.py		setup.py
update-version.sh		update-version.sh