A library of tools for fuzzy rough machine learning.
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
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