2 papers
cs.LG2026
path_boost: A Python Package for Interpretable Graph-Level Prediction using Path-Based Gradient Boosting
Claudio Meggio, Johan Pensar, Riccardo De Bin
We present path_boost, a Python package for interpretable supervised learning on graph-structured input data. The package implements PathBoost, a gradient boosting algorithm that a…
cs.LG2026
Path-Based Gradient Boosting for Graph-Level Prediction
Claudio Meggio, Johan Pensar, Riccardo De Bin
We propose PathBoost, a gradient tree boosting method for graph-level classification and regression that learns discriminative path-based features directly from the input graph str…