Kernel of Partition Paths: A Unified Representation for Tree Ensembles
A recent line of work has reframed individual decision trees as linear models on engineered features associated with their splits, opening routes for oracle inequalities and feature-importance reinterpretation, but leaving open the question of what unified geometric object a forest induces when one indexes its feature map by nodes rather than by splits. The present paper studies that object. KPP indexes the feature map by the nodes of the forest, weighted by a path metric that turns each coordinate into a component of a squared-Euclidean path-isometric embedding. KPP unifies four pillars under a single node-indexed representation whose Gram is non-diagonal and carries a metric: prediction...
| Authors | Nicolas Mahler |
|---|---|
| Primary category | stat.ML |
| Published | 17 June 2026 |
| Last updated at source | 10 July 2026 |
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