English

Possibility results for graph clustering: A novel consistency axiom

Machine Learning 2022-04-05 v6 Machine Learning

Abstract

Kleinberg introduced three natural clustering properties, or axioms, and showed they cannot be simultaneously satisfied by any clustering algorithm. We present a new clustering property, Monotonic Consistency, which avoids the well-known problematic behaviour of Kleinberg's Consistency axiom, and the impossibility result. Namely, we describe a clustering algorithm, Morse Clustering, inspired by Morse Theory in Differential Topology, which satisfies Kleinberg's original axioms with Consistency replaced by Monotonic Consistency. Morse clustering uncovers the underlying flow structure on a set or graph and returns a partition into trees representing basins of attraction of critical vertices. We also generalise Kleinberg's axiomatic approach to sparse graphs, showing an impossibility result for Consistency, and a possibility result for Monotonic Consistency and Morse clustering.

Keywords

Cite

@article{arxiv.1806.06142,
  title  = {Possibility results for graph clustering: A novel consistency axiom},
  author = {Fabio Strazzeri and Rubén J. Sánchez-García},
  journal= {arXiv preprint arXiv:1806.06142},
  year   = {2022}
}

Comments

Minor changes, bibliography updated