Data

Tools

Indexes

Applications

Experiments

Open Source Science

mulearn

A python package for inducing membership functions from labeled data

https://github.com/slimlaboratory/mulearn

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

A python package for inducing membership functions from labeled data

Basic Info
  • Host: GitHub
  • Owner: SLIMlaboratory
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 12.9 MB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 4
  • Open Issues: 0
  • Releases: 26
Created over 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Citation

README.md

mulearn

Documentation Status

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 running pip install mulearn in a terminal;
  • cloning this repo.

APIs are described at https://mulearn.readthedocs.io/.

Owner

  • Name: SLIMlaboratory
  • Login: SLIMlaboratory
  • Kind: organization

Citation (CITATION.cff) 

authors:
  - family-names: Malchiodi
    given-names: Dario

identifiers:
  - description: "This is the collection of archived snapshots of all versions of My Research Software"
    type: doi
    value: https://doi.org/10.1007/978-3-319-03200-9_6

license: Apache-2.0
repository-code: "https://github.com/Absinthe31/mulearn"
title: "mulearn"
version: 0.1.8

GitHub Events

Total
  • Fork event: 1
Last Year
  • Fork event: 1

Dependencies

v0.1.8/docs/Gemfile rubygems
  • github-pages >= 0 development
  • jekyll ~> 3.7
v0.1.8/docs/Gemfile.lock rubygems
  • activesupport 4.2.11.1
  • addressable 2.7.0
  • coffee-script 2.4.1
  • coffee-script-source 1.11.1
  • colorator 1.1.0
  • commonmarker 0.17.13
  • concurrent-ruby 1.1.5
  • dnsruby 1.61.3
  • em-websocket 0.5.1
  • ethon 0.12.0
  • eventmachine 1.2.7
  • execjs 2.7.0
  • faraday 0.17.0
  • ffi 1.11.3
  • forwardable-extended 2.6.0
  • gemoji 3.0.1
  • github-pages 202
  • github-pages-health-check 1.16.1
  • html-pipeline 2.12.2
  • http_parser.rb 0.6.0
  • i18n 0.9.5
  • jekyll 3.8.5
  • jekyll-avatar 0.6.0
  • jekyll-coffeescript 1.1.1
  • jekyll-commonmark 1.3.1
  • jekyll-commonmark-ghpages 0.1.6
  • jekyll-default-layout 0.1.4
  • jekyll-feed 0.11.0
  • jekyll-gist 1.5.0
  • jekyll-github-metadata 2.12.1
  • jekyll-mentions 1.4.1
  • jekyll-optional-front-matter 0.3.0
  • jekyll-paginate 1.1.0
  • jekyll-readme-index 0.2.0
  • jekyll-redirect-from 0.14.0
  • jekyll-relative-links 0.6.0
  • jekyll-remote-theme 0.4.0
  • jekyll-sass-converter 1.5.2
  • jekyll-seo-tag 2.5.0
  • jekyll-sitemap 1.2.0
  • jekyll-swiss 0.4.0
  • jekyll-theme-architect 0.1.1
  • jekyll-theme-cayman 0.1.1
  • jekyll-theme-dinky 0.1.1
  • jekyll-theme-hacker 0.1.1
  • jekyll-theme-leap-day 0.1.1
  • jekyll-theme-merlot 0.1.1
  • jekyll-theme-midnight 0.1.1
  • jekyll-theme-minimal 0.1.1
  • jekyll-theme-modernist 0.1.1
  • jekyll-theme-primer 0.5.3
  • jekyll-theme-slate 0.1.1
  • jekyll-theme-tactile 0.1.1
  • jekyll-theme-time-machine 0.1.1
  • jekyll-titles-from-headings 0.5.1
  • jekyll-watch 2.2.1
  • jemoji 0.10.2
  • kramdown 2.3.0
  • liquid 4.0.0
  • listen 3.1.5
  • mercenary 0.3.6
  • mini_portile2 2.4.0
  • minima 2.5.0
  • minitest 5.13.0
  • multipart-post 2.1.1
  • nokogiri 1.10.8
  • octokit 4.14.0
  • pathutil 0.16.2
  • public_suffix 3.1.1
  • rb-fsevent 0.10.3
  • rb-inotify 0.10.0
  • rouge 3.11.0
  • ruby-enum 0.7.2
  • ruby_dep 1.5.0
  • rubyzip 2.0.0
  • safe_yaml 1.0.5
  • sass 3.7.4
  • sass-listen 4.0.0
  • sawyer 0.8.2
  • terminal-table 1.8.0
  • thread_safe 0.3.6
  • typhoeus 1.3.1
  • tzinfo 1.2.5
  • unicode-display_width 1.6.0
environment.yml conda
  • docutils 0.16
  • gurobi 9.1.*
  • ipython 7.19.*
  • ipywidgets 7.5.*
  • jupyter_client 6.1.*
  • jupyter_core 4.7.*
  • keras-preprocessing 1.1.*
  • markdown 3.3.*
  • matplotlib 3.3.*
  • matplotlib-base 3.3.*
  • nbclient 0.5.*
  • nbconvert 6.0.*
  • nbformat 5.0.*
  • numpy 1.19.*
  • oauthlib 3.0.*
  • openssl 1.1.*
  • pandas 1.1.*
  • pip 20.3.*
  • plotly 4.14.*
  • plotly-orca 1.3.*
  • psutil 5.8.*
  • pyqt 5.12.*
  • python 3.7.*
  • python-dateutil 2.8.*
  • scikit-learn 0.23.*
  • scipy 1.6.*
  • sphinx 3.3.*
  • sphinx-math-dollar 1.2.*
  • tensorboard 2.4.*
  • tensorflow 2.3.*
  • tensorflow-base 2.3.*
  • tqdm 4.54.*
  • zeromq 4.3.*
setup.py pypi
v0.1.8/setup.py pypi