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Experimental variation of scikit-ExSTraCS that allows the user to import an initial rule population that will get initially evaluated and assigned fitness values prior to the start of learning iterations. This allows for the import of manually curated expert knowledge derived rules, or rules derived from other sources.

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UrbsLab/scikit-ExSTraCS-RuleInit

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scikit-ExSTraCS-RuleInit

The scikit-ExSTraCS-RuleInit repository includes (1) a python file (named RFI-LCS Rule Loading Function.py) showing how to import an initial rule populaiton prior to the start of ExStraCS learning iterations, which allows for the import of manually curated expert knowledge derived rules, and (2) a python file (named RFI-LCS.py) with a Random Forest Initialized Learning Classifier System (RFI-LCS), which converts branches from a Random Forest model to rules used to intialize ExSTraCS. RFI-LCS is an experimental algorithm that is under active development and testing.

Please see the scikit-ExSTraCS package for more details about ExSTraCS.

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Experimental variation of scikit-ExSTraCS that allows the user to import an initial rule population that will get initially evaluated and assigned fitness values prior to the start of learning iterations. This allows for the import of manually curated expert knowledge derived rules, or rules derived from other sources.

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