Graph explorer

Hausdorff clustering

A clustering algorithm based on the Hausdorff distance is introduced and compared to the single and complete linkage. The three clustering procedures are applied to a toy example and to the time series of financial data. The dendrograms are scrutinized and their features confronted. The Hausdorff linkage relies of firm mathematical grounds and turns out to be very effective when one has to discriminate among complex structures.

11 nodes13 linksoverview previewHausdorff clustering
11 nodes13 links
Hausdorff clustering11 visible / 11 total nodes / 28 links
Co-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipRelated contextAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalTopic signalRelated contextRelated contextAuthorshipAuthorshipWHausdorff clusteringpreprint / 2008AN. BasaltoResearcherAR. BellottiResearcherAF. De CarloResearcherAP. FacchiResearcherTcond-mat.stat-mech6570 worksTphysics.soc-ph3139 worksTphysics.data-an1229 worksTq-fin.ST472 worksAE. PantaleoResearcherAS. PascazioResearcher
PaperSignal 1010 links

Hausdorff clustering

preprint / 2008

Open