Adaptative initialisation of a EvKNN classification algorithm - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Adaptative initialisation of a EvKNN classification algorithm

Résumé

The establishment of the learning data base is a long and tedious task that must be carried out before starting the classification process. An Evidential KNN (EvKNN) has been developed in order to help the user, which proposes the "best" samples to label according to a strategy. However, at the beginning of this task, the classes are not clearly defined and are represented by a number of labeled samples smaller than the k required samples for EvKNN. In this paper, we propose to take into account the available information on the classes using an adapted evidential model. The algorithm presented in this paper has been tested on the classification of an image collection.
Fichier principal
Vignette du fichier
12_Belief_Chan.pdf (295.23 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00679148 , version 1 (12-12-2014)

Identifiants

  • HAL Id : hal-00679148 , version 1

Citer

Stefen Chan Wai Tim, Michèle Rombaut, Denis Pellerin. Adaptative initialisation of a EvKNN classification algorithm. Belief 2012 - 2nd International Conference on Belief Functions, May 2012, Compiègne, France. pp.n/a. ⟨hal-00679148⟩
176 Consultations
94 Téléchargements

Partager

Gmail Facebook X LinkedIn More