https://github.com/starling-lab/boostsrl

BoostSRL: "Boosting for Statistical Relational Learning." A gradient-boosting based approach for learning different types of SRL models.
https://github.com/starling-lab/boostsrl

artificial-intelligence machine-learning machine-learning-algorithms pattern-classification statistical-learning

Last synced: 10 months ago
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BoostSRL: "Boosting for Statistical Relational Learning." A gradient-boosting based approach for learning different types of SRL models.

• Host: GitHub
• URL: https://github.com/starling-lab/boostsrl
• Owner: starling-lab
• License: gpl-3.0
• Created: 2016-12-20T20:42:34.000Z (about 9 years ago)
• Default Branch: development
• Last Pushed: 2023-09-11T14:11:18.000Z (over 2 years ago)
• Last Synced: 2025-04-06T05:51:59.647Z (10 months ago)
• Topics: artificial-intelligence, machine-learning, machine-learning-algorithms, pattern-classification, statistical-learning
• Language: Java
• Homepage: https://starling.utdallas.edu
• Size: 21.3 MB
• Stars: 32
• Watchers: 18
• Forks: 22
• Open Issues: 20
• Metadata Files:
  • Readme: README.md
  • Contributing: .github/CONTRIBUTING.md
  • License: license.txt
  • Code of conduct: .github/CODE_OF_CONDUCT.md

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README

          
# BoostSRL - v1.1

*BoostSRL (Boosting for Statistical Relational Models) is a gradient-boosting based approach to learning different types of SRL models.*

As with the standard gradient-boosting approach, our approach turns the model-learning problem to learning a sequence of regression models. The key difference to the standard approaches is that we learn relational regression models (i.e. regression models that operate on relational data). We assume the data to be in predicate-logic format and the output are essentially first-order regression trees where the inner nodes contain conjunctions of logical predicates.

Developed by [Jude Shavlik](http://pages.cs.wisc.edu/~shavlik/), [Tushar Khot](http://pages.cs.wisc.edu/~tushar/), [Sriraam Natarajan](http://utdallas.edu/~sxn177430/), and [members of the StARLinG Lab](https://starling.utdallas.edu/people/).

Contact: **Sriraam.Natarajan@utdallas.edu**

---

| `Latest Release` | `License` | `Wiki` | `Website` | `Downloads` | `Datasets` |

| :---: | :---: | :---: | :---: | :---: | :---: |

| [![][release img]][release] | [![][license img]][license] | [BoostSRL Wiki](https://starling.utdallas.edu/software/boostsrl/wiki/) | [Group Website](https://starling.utdallas.edu) | [Downloads](https://github.com/boost-starai/BoostSRL-Misc/tree/master/VersionHistory/Version1.0) | [Datasets](https://github.com/boost-starai/BoostSRL-Misc/tree/master/Datasets) |

### New in Version 1.1

* Discretization of continuous variables

* Relational random walks (grounded and lifted)

## Getting Started

**Prerequisites**:

* Java (tested with *openjdk 1.8.0_144*)

**Installation**:

* Download stable jar file.  

* Download stable source with git.  

  `git clone -b master https://github.com/boost-starai/BoostSRL.git`

* Nightly builds with git.  

  `git clone -b development https://github.com/boost-starai/BoostSRL.git`

  

## Basic Usage



BoostSRL assumes that data are contained in files with data structured in predicate-logic format.

*Positive Examples:*

    father(harrypotter,jamespotter).

	father(ginnyweasley,arthurweasley).

	father(ronweasley,arthurweasley).

	...

*Negative Examples:*

	father(harrypotter,mollyweasley).

	father(harrypotter,lilypotter).

	father(harrypotter,ronweasley).

	...

*Facts:*

	male(harrypotter).

	male(jamespotter).

	siblingof(ronweasley,fredweasley).

	siblingof(ronweasley,georgeweasley).

	childof(jamespotter,harrypotter).

	childof(lilypotter,harrypotter).

	...

*Learning a Relational Dependency Network:*

    [~/BoostSRL/]$ java -jar v1-0.jar -l -train train/ -target father -trees 10

*Inference with the Relational Dependency Network:*

    [~/BoostSRL/]$ java -jar v1-0.jar -i -model train/models/ -test test/ -target father -trees 10

## Contributing

Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for documentation on submitting issues and pull requests.

## Versioning

We use [Semantic Versioning (Major.Minor.Patch)](http://semver.org/) for versioning. See [Releases](https://github.com/boost-starai/BoostSRL/releases) for all stable versions that are available, associated documentation can be found via the changelog.

## Acknowledgements

We would like to thank our users, our supporters, and Professor Natarajan.

[license]:license.txt

[license img]:https://img.shields.io/github/license/boost-starai/BoostSRL.svg

[release]:https://github.com/boost-starai/BoostSRL/releases

[release img]:https://img.shields.io/github/tag/boost-starai/BoostSRL.svg