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| HAL : hal-00679148, version 1 |
| Fiche détaillée |  Récupérer au format |
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| 2nd International Conference on Belief Functions (Belief 2012), Compiègne : France (2012) |
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| Adaptative initialisation of a EvKNN classification algorithm |
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| Stefen Chan Wai Tim 1Michele Rombaut 1 |
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| (09/05/2012) |
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| 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. |
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| 1 : | Grenoble Images Parole Signal Automatique (GIPSA-lab) |
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CNRS : UMR5216 – Université Joseph Fourier - Grenoble I – Université Pierre-Mendès-France - Grenoble II – Université Stendhal - Grenoble III – Institut Polytechnique de Grenoble - Grenoble Institute of Technology |
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| agpig |
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| Domaine | : | Informatique/Traitement du signal et de l'image Sciences de l'ingénieur/Traitement du signal et de l'image |
| hal-00679148, version 1 | |
| http://hal.archives-ouvertes.fr/hal-00679148 | |
| oai:hal.archives-ouvertes.fr:hal-00679148 | |
| Contributeur : Michele Rombaut | |
| Soumis le : Mercredi 14 Mars 2012, 18:43:41 | |
| Dernière modification le : Jeudi 15 Mars 2012, 16:36:10 | |
