Clustering on Manifolds with Dual-Rooted Minimal Spanning Trees

Abstract : In this paper, we introduce a new distance computed from the construction of dual-rooted minimal spanning trees (MSTs). This distance extends Grikschat's approach, exhibits attractive properties and allows to account for both local and global neighborhood information. Furthermore, a function measuring the probability that a point belongs to a detected class is proposed. Some connections with diffusion maps are outlined. The dual-rooted tree-based distance (DRPT) allows us to construct a new affinity matrix for use in a spectral clustering algorithm, or leads to a new data analysis method. Results are presented on benchmark datasets.
Document type :
Conference papers
Liste complète des métadonnées

Cited literature [18 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00492745
Contributor : Laurent Galluccio <>
Submitted on : Monday, July 19, 2010 - 4:30:01 PM
Last modification on : Thursday, February 7, 2019 - 5:55:28 PM
Document(s) archivé(s) le : Friday, October 22, 2010 - 4:19:54 PM

File

GallMC10aalborg.pdf
Explicit agreement for this submission

Identifiers

  • HAL Id : hal-00492745, version 2

Collections

Citation

Laurent Galluccio, Olivier Michel, Pierre Comon. Clustering on Manifolds with Dual-Rooted Minimal Spanning Trees. 16th European Signal Processing Conference EUSIPCO-2010, Aug 2010, Aalborg, Denmark, France. ⟨hal-00492745v2⟩

Share

Metrics

Record views

343

Files downloads

95