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:
- via
pip, by runningpip install mulearnin a terminal; - cloning this repo.
APIs are described at https://mulearn.readthedocs.io/.
1 maintainer
Release files for mulearn 1.1.3
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Source distribution (sdist)
| File | Size | Uploaded | |
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| mulearn-1.1.3.tar.gz | 514.1 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mulearn-1.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 538.2 kB
Release files / mulearn-1.1.3.tar.gz
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