ClustGeo : Classification Ascendante Hiérarchique (CAH) avec contraintes de proximitté géographique
hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
dc.contributor.author | CHAVENT, Marie | |
hal.structure.identifier | Environnement, territoires et infrastructures [UR ETBX] | |
dc.contributor.author | KUENTZ-SIMONET, Vanessa | |
hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
hal.structure.identifier | Environnement, territoires et infrastructures [UR ETBX] | |
dc.contributor.author | LABENNE, Amaury | |
hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Ecole Nationale Supérieure de Cognitique [ENSC] | |
dc.contributor.author | SARACCO, Jerome | |
dc.date.accessioned | 2024-04-04T03:16:38Z | |
dc.date.available | 2024-04-04T03:16:38Z | |
dc.date.conference | 2015-06-01 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/194233 | |
dc.description.abstractEn | Hierarchical Ascendant Clustering (HAC) is a well-known method of individual clustering. This method aims to bring together individuals who are similar regarding to variables which describe them. But when individuals are geographical units, the user may wish geographically close individuals to be put in same clusters and that, without too much deteriorating the quality of the partition. The proposed ClustGeo method allows geographical constraints of proximity to be taken into account within the HAC. For that purpose, a new Ward homogeneity criterion based on two different matrices of distances is proposed. | |
dc.language.iso | fr | |
dc.title | ClustGeo : Classification Ascendante Hiérarchique (CAH) avec contraintes de proximitté géographique | |
dc.title.en | ClustGeo: Ascendant Hierarchical Clustering (AHC) with geographical constraints | |
dc.type | Communication dans un congrès | |
dc.subject.hal | Statistiques [stat]/Machine Learning [stat.ML] | |
dc.subject.hal | Statistiques [stat]/Applications [stat.AP] | |
dc.subject.hal | Statistiques [stat]/Méthodologie [stat.ME] | |
bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.conference.title | 47èmes Journées de Statistique de la SFdS | |
bordeaux.country | FR | |
bordeaux.conference.city | Lille | |
bordeaux.peerReviewed | oui | |
hal.identifier | hal-01246856 | |
hal.version | 1 | |
hal.invited | non | |
hal.proceedings | oui | |
hal.popular | non | |
hal.audience | Nationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-01246856v1 | |
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