Skip to main content

A package to build an optimal binary decision tree classifier.

Project description

Travis CircleCI ReadTheDocs Codecov


Gaël Aglin, Siegfried Nijssen, Pierre Schaus

Relevant paper: [DL852020]

This project implements an algorithm for inferring optimal binary decision trees. It is scikit-learn compatible and can be used in combination with scikit-learn. As a scikit-learn classifier, it implements the methods “fit” and “predict”.

This tool can be installed in two ways:

  • download the source from github and install using the command python3 install in the root folder

  • install from pip by using the command pip install dl8.5 in the console

Disclaimer: The compilation of the project has been tested with C++ compilers on the Linux and MacOS operating systems; Windows is not yet supported.


Aglin, G., Nijssen, S., Schaus, P. Learning optimal decision trees using caching branch-and-bound search. In AAAI. 2020.

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

dl8.5-0.0.15.tar.gz (38.3 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page