pydl8.5 0.1.2

A package to build an optimal binary decision tree classifier.

Authors:

Gaël Aglin, Siegfried Nijssen, Pierre Schaus

Relevant paper : [DL852020] [PYDL852020]

The PyDL8.5 library providing an implementation of DL8.5 algorithm. Please read the relevant articles referenced below to learn about the additional features. Please cite these papers if you used the current library. The documentation will help you get started with PyDL8.5.

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”.

The current version of PyDL8.5 is an optimized one using some ideas from MurTree paper listed in CHANGES.txt. The version of the code used in the AAAI paper [DL852020] is v0.0.15.

This tool can be installed in two ways:

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

• install from pip by using the command pip install pydl8.5 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.

[DL852020]

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

[PYDL852020]

Aglin, G., Nijssen, S., Schaus, P. PyDL8.5: a Library for Learning Optimal Decision Trees., In IJCAI. 2020.