A library of tools for fuzzy rough machine learning.
Project description
fuzzy-rough-learn
fuzzy-rough-learn is a library of fuzzy rough machine learning algorithms, extending scikit-learn.
Contents
At present, fuzzy-rough-learn contains the following algorithms:
Classifiers
Fuzzy Rough Nearest Neighbours (FRNN; multiclass)
Fuzzy Rough OVO COmbination (FROVOCO; muliclass, suitable for imbalanced data)
Fuzzy ROugh NEighbourhood Consensus (FRONEC; multilabel)
Preprocessors
Fuzzy Rough Feature Selection (FRFS)
Fuzzy Rough Prototype Selection (FRPS)
Utilities
OWA operator class
Nearest Neighbour search algorithm class
Documentation
The documentation is located here.
Dependencies
fuzzy-rough-learn requires python 3.7+ and the following packages:
scipy >= 1.1.0
numpy >=1.16.0
scikit-learn >=0.22.0
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