Skip to main content

Python wrappers for using BoostSRL jar files.

Project description

Repository preview image: "srlearn. Python wrappers around BoostSRL with a scikit-learn-style interface. pip install srlearn."

License LGTM code quality analysis Travis CI continuous integration build status AppVeyor Windows build status Code coverage status CircleCI Documentation status

srlearn is a set of Python wrappers around BoostSRL with a scikit-learn interface.

Getting Started


  • Java 1.8

  • Python (3.6, 3.7)


pip install srlearn

Basic Usage

The general setup should be similar to scikit-learn. But there are a few extra requirements in terms of setting background knowledge and formatting the data.

A minimal working example (using the Toy-Cancer data set imported with ‘example_data’) is:

>>> from srlearn.rdn import BoostedRDN
>>> from srlearn import Background
>>> from srlearn import example_data
>>> bk = Background(
...     modes=example_data.train.modes,
...     use_std_logic_variables=True,
... )
>>> clf = BoostedRDN(
...     background=bk,
...     target='cancer',
... )
>>> clf.predict_proba(example_data.test)
array([0.88079619, 0.88079619, 0.88079619, 0.3075821 , 0.3075821 ])
>>> clf.classes_
array([1., 1., 1., 0., 0.])

example_data.train and example_data.test are each srlearn.Database objects, so this hides some of the complexity behind the scenes.

This example abstracts away some complexity in exchange for compactness. For more examples, see the Example Gallery.


We have adopted the Contributor Covenant Code of Conduct version 1.4. Please read, follow, and report any incidents which violate this.

Questions, Issues, and Pull Requests are welcome. Please refer to for information on submitting issues and pull requests.

Versioning and Releases

We use SemVer for versioning. See Releases for stable versions that are available, or the Project Page on PyPi.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

srlearn-0.5.0.tar.gz (4.1 MB view hashes)

Uploaded source

Built Distribution

srlearn-0.5.0-py3-none-any.whl (4.1 MB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page