o o o o o | o | |\ /| | / | o-o o--o o-o oo | | O | oo o-o OO o-o o o | | | | | | | | | | | | | | | | \ | | \ / O---oo-o o--O | o-o o-o-o o o o-o-o o o o-o o | o--o o--o o o--o o o | | | | o | | O-Oo oo o-o o-O o-o o-O-o O-o o-o | o-O o-o | \ | | | | | | | | | | | | | |-' | | | \ o o o-o-o o o-o o-o o o o o | o-o o o-o o-o Logical Markov Random Fields.
This is a companion project for the LoMRF (Logical Markov Random Fields) which contains example files (sample knowledge bases and evidence data), as well as files that are needed for Unit testing LoMRF. LoMRF is an open source implementation of Markov Logic Networks (MLNs).
Please note that all example files are part of the documentation of LoMRF. The example files are separated into the following categories:
- Files for performing probabilistic inference (see Probabilistic Inference Documentation).
- Files for weight learning (see Weight Learning Documentation).
- Files for structure learning (see Structure Learning Documentation).
- A collection of sample files that represent input example cases for Unit Tests.
LoMRF comes with ABSOLUTELY NO WARRANTY. This is free software, and you are welcome to redistribute it under certain conditions; See the GNU Lesser General Public License v3 for more details.