scikit-tree

scikit-tree extends the Cython implementation of a decision tree learner from scikit-learn.

The general rationale is as follows:

1. scikit-learn’s codebase is fast and heavily tested. Relying on their implementation of a tree data structures makes it easier to extend to new methods without worrying about edge cases in the tree code.

2. Cython offers a nice tradeoff between high-level code (readability, maintainability, syntactic sugar, etc…) and low-level code (direct memory access / management, GIL release, etc…)

The initial version of this project is just an extraction of the scikit-learn tree code into a minimum-viable python library. As a result, the build system largely follows that of the scikit-learn-contrib project template rather than the scikit-learn build infrastructure.