Relational Functional Gradient Boosting in Python.
rfgb: Relational Functional Gradient Boosting (in Python).
- Documentation: https://rfgb.readthedocs.io/en/latest/
- Questions? Contact Alexander L. Hayes (hayesall)
Stable builds may be installed from PyPi
pip install rfgb
Or develop further by cloning the repository
git clone https://github.com/hayesall/rfgb.git cd rfgb/ python setup.py develop
Learning with a relational dependency network.
cd testDomains/Logistics/ rfgb init rfgb learn rdn -target unload
Additional options for each subcommand may be viewed by passing -h as a parameter.
rfgb -h rfgb learn rdn -h
Classification with Expert Advice (-advice)
Preferred and non-preferred labels may be provided as advice during classification via logical rules. This advice may be specified in a file named advice.txt in the train directory for a dataset.
Four datasets (BlocksWorld, HeartAttack, Logistics, and MoodDisorder) have an advice file included for demonstration
cd testDomains/Logistics/ rfgb init rfgb learn rdn -advice -target unload
cd testDomains/HeartAttack/ rfgb init rfgb learn rdn -advice -target ha
“Targets” specify what is learned, examples of the target are provided in pos.txt, neg.txt, or examples.txt (for regression). These are specified here for convenience.
|TicTacToe||put or dontput|
- Test cases (codecov >90%)
- General interaction improvements for commandline and library
- Learning Markov Logic Networks
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
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