arXiv Machine Learning

Revisiting Forest Proximities via Sparse Leaf-Incidence Kernels

arXiv:2601. 02735v3 Announce Type: replace Abstract: Decision forests induce supervised similarities through the partition structure of their trees.

arXiv AI
Jul 7

SilvaScenes: Tree Detection and Species Classification from Under-Canopy Images in Natural Forests

arXiv:2510. 09458v2 Announce Type: replace-cross Abstract: Interest in forestry automation is growing alongside rapid advances in deep learning.

By David-Alexandre Duclos, William Guimont-Martin, Gabriel Jeanson, Arthur Larochelle-Tremblay, Martine Lapointe, Th\'eo Defosse, Fr\'ed\'eric Moore, Philippe Nolet, Fran\c{c}ois Pomerleau, Philippe Gigu\`ere
arXiv Machine Learning
Jun 18

Kernel of Partition Paths: A Unified Representation for Tree Ensembles

arXiv:2606. 18853v1 Announce Type: cross Abstract: 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.

By Nicolas Mahler
arXiv Machine Learning
Jul 28

An Integrated Deep Learning and Statistical Framework for Whole-Network Gene--Environment Association with Leaf Vascular Architecture

arXiv:2607. 22763v1 Announce Type: new Abstract: Leaf veins exhibit remarkable diversity in architecture and patterning, yet existing gene--environment association studies have primarily quantified leaf venation using a small collection of low-dimensional summary traits, thereby discarding most of the structural information contained in the original images.

By Geran Zhao, Yangsheng Wang, Xiaotian Dai, Guifang Fu
arXiv Machine Learning
Aug 6

ArborEnum: Decision Tree Rashomon Sets over Continuous Features

arXiv:2608. 04310v1 Announce Type: new Abstract: The Rashomon effect describes the phenomenon that many models can achieve nearly equivalent performance on the same learning task, with significant ramifications for robustness, feature importance, and customizability.

By Zakk Heile, Hayden McTavish, Margo Seltzer, Cynthia Rudin
arXiv Machine Learning
Jun 3

How Many Trees in a Random Forest? A Revisited Approach with Plateau Search and Optuna Integration

arXiv:2606. 03549v1 Announce Type: new Abstract: Hyperparameter optimization (HPO) for Random Forest faces a specific difficulty in tuning the number of trees: the predictive score typically improves monotonically with ensemble size, so standard methods such as Tree-structured Parzen Estimator (TPE) and Hyperband require a predefined search range and often drive the estimate toward its right boundary.

By Vadim Porvatov, Andrey Dukhovny, Andrey Lange
arXiv Machine Learning
Jun 15

NEST3D: A High-Resolution Multimodal Dataset of Sociable Weaver Tree Nests

arXiv:2606. 14562v1 Announce Type: cross Abstract: Sociable weaver nests function as complex ecological structures offering thermoregulatory microhabitats and sustaining diverse species; however, datasets used in prior studies lack fine-grained 3D structural detail.

By Constanza A. Molina Catricheo, Simon Boeder, Ting-Jia Guo, Giacomo May, Cl\'ement Berthelot, Devis Tuia, Friedrich Fedor Reinhard, Fabio Remondino, Benjamin Risse