An Empirical Comparison of Evidential Reasoning, Linear Discriminant Analysis, and Maximum Likelihood Algorithms for Alpine Land Cover Classification
作者： Derek R. Peddle
DOI: 10.1080/07038992.1993.10855148
关键词:
摘要: RESUMELa mise au point de nouvelles methodes d'analyse des donnees teledetection actuelles et futures est necessaire si l'on veut surmonter les limites que presentent classiques traitement classification images. Dans le present article, l'auteur fait l'evaluation d'un classificateur par raisonnement d'evidences [Evidential Reasoning] (MERCURY⊕) qui appel a la theorie evidences Dempster-Shafer offre une souplesse accrue ainsi qu 'une nouvelle fonctionnalite pour traiter ensembles presentant proprietes statistiques diverses, dimensions superieures, l'incertitude echelles mesures differentes, facteurs dejouent algorithmes maximum vraisemblance discriminante lineaire. Le fondement theorique du compare aux deux precitees. Suit ensuite comparaison empirique approfondie trois classificateurs, fondee sur serie tests pour...
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