srlearn: A Python Library for Gradient-Boosted Statistical Relational Models

2019/12/17 by Hayes, Alexander L.
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)

paper · doi:10.48550/arxiv.1912.08198

Abstract

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.

Related

• pystacked: Stacking generalization and machine learning in Stata
• pystacked: Stacking generalization and machine learning in Stata
• Learning Models over Relational Data: A Brief Tutorial
• shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python
• Induction of Interpretable Possibilistic Logic Theories from Relational\n Data