Skip to main content

A library of tools for fuzzy rough machine learning.

Project description

Travis AppVeyor Codecov CircleCI ReadTheDocs


fuzzy-rough-learn is a library of fuzzy rough machine learning algorithms, extending scikit-learn.


At present, fuzzy-rough-learn contains the following algorithms:


  • Fuzzy Rough Nearest Neighbours (FRNN; multiclass)
  • Fuzzy Rough OVO COmbination (FROVOCO; muliclass, suitable for imbalanced data)
  • Fuzzy ROugh NEighbourhood Consensus (FRONEC; multilabel)


  • Fuzzy Rough Feature Selection (FRFS)
  • Fuzzy Rough Prototype Selection (FRPS)


  • OWA operator class
  • Nearest Neighbour search algorithm class


The documentation is located here.


fuzzy-rough-learn requires python 3.7+ and the following packages:

  • scipy >= 1.1.0
  • numpy >=1.16.0
  • scikit-learn >=0.22.0

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for fuzzy-rough-learn, version 0.1.0
Filename, size File type Python version Upload date Hashes
Filename, size fuzzy-rough-learn-0.1.0.tar.gz (12.9 MB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page