FOSC-X: An Extended Framework for Optimal Local Cuts and Non-Horizontal Cluster Selection from Clustering Hierarchies

arXiv:2606.18972 · stat.ML, cs.LG · Submitted 2026-06-17 · Read on arXiv

Connor Simpson, Ricardo J. G. B. Campello

stat.ML, cs.LG

Submitted: 2026-06-17

Code: https://github.com/Campello-Lab/FOSC-X

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Clustering — 214× in this paper · explained in 2 episodes
Pruning — 28× in this paper · explained in 4 episodes
Objective Function — 14× in this paper · explained in 2 episodes
Hierarchical Structure — 7× in this paper · explained in 3 episodes
Benchmark — 4× in this paper · explained in 2 episodes
Adjusted Mutual Information — 3× in this paper
Excess of Mass — 3× in this paper
Interpretability — 3× in this paper · explained in 15 episodes
Mutual Information — 3× in this paper · explained in 2 episodes
Robustness — 2× in this paper · explained in 6 episodes
Benchmarking — 1× in this paper · explained in 4 episodes
Computational Biology — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Downstream Tasks — 1× in this paper · explained in 2 episodes
Framework for Optimal Selection of Clusters — 1× in this paper
Linear Complexity — 1× in this paper · explained in 2 episodes
Linear Time Complexity — 1× in this paper · explained in 2 episodes
Modularity — 1× in this paper · explained in 9 episodes
Pairwise Comparisons — 1× in this paper · explained in 2 episodes
Papers — 1× in this paper · explained in 3 episodes
Unsupervised Learning — 1× in this paper · explained in 2 episodes

Sources

Adaptive cut reveals multiscale complexity in networks

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