srlearn: A Python Library for Gradient-Boosted Statistical Relational Models
arXiv:1912.08198v1
Originality Synthesis-oriented
AI Analysis
This provides a tool for researchers and practitioners working with statistical relational learning, but it is incremental as it builds on existing methods and interfaces.
The authors tackled the problem of implementing gradient-boosted statistical relational models by developing srlearn, a Python library that adapts the scikit-learn interface for learning and inference tasks.
We present srlearn, a Python library for boosted statistical relational models. We adapt the scikit-learn interface to this setting and provide examples for how this can be used to express learning and inference problems.