LoMRF alternatives and similar packages
Based on the "Science and Data Analysis" category.
Alternatively, view LoMRF alternatives based on common mentions on social networks and blogs.
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Zeppelin
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FACTORIE
FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference. -
ND4S
DISCONTINUED. ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J. -
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Clustering4Ever
C4E, a JVM friendly library written in Scala for both local and distributed (Spark) Clustering. -
rscala
The Scala interpreter is embedded in R and callbacks to R from the embedded interpreter are supported. Conversely, the R interpreter is embedded in Scala. -
InfluxDB - Purpose built for real-time analytics at any scale.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
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Logical Markov Random Fields.
LoMRF: Logical Markov Random Fields
LoMRF is an open-source implementation of Markov Logic Networks (MLNs) written in Scala programming language.
Features overview:
- Parallel grounding algorithm based on Akka Actors library.
- Marginal (MC-SAT) and MAP (MaxWalkSAT and LP-relaxed Integer Linear Programming) inference (lomrf infer).
- Batch and on-line Weight Learning (Max-Margin, AdaGrad and CDA) (lomrf wlearn).
- On-line Structure Learning (OSL and OSLa) (lomrf slearn).
- MLN knowledge base compilation (lomrf compile):
- Predicate completion.
- Clausal form transformation.
- Replacement of functions with utility predicates and vice versa.
- Reads and produces Alchemy compatible MLN files.
- Can export ground MRF in various formats (lomrf export).
- Can compare MLN theories (lomrf diff).
- Online supervision completion on semi-supervised training sets [currently experimental] (lomrf supervision)
Documentation
Latest [documentation](docs/index.md).
Contributions
Contributions are welcome, for details see [CONTRIBUTING.md](CONTRIBUTING.md).
License
Copyright (c) 2014 - 2019 Anastasios Skarlatidis and Evangelos Michelioudakis
LoMRF is licensed under the Apache License, Version 2.0: https://www.apache.org/licenses/LICENSE-2.0
Reference in Scientific Publications
Please use the following BibTex entry when you cite LoMRF in your papers:
@misc{LoMRF,
author = {Anastasios Skarlatidis and Evangelos Michelioudakis},
title = {{Logical Markov Random Fields (LoMRF): an open-source implementation of Markov Logic Networks}},
url = {https://github.com/anskarl/LoMRF},
year = {2014}
}
*Note that all licence references and agreements mentioned in the LoMRF README section above
are relevant to that project's source code only.