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Título:
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Accuracy Assessment for Soft Classification Maps
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Autores:
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Gómez, Daniel ;
Biging, Greg ;
Montero, Javier
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Tipo de documento:
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texto impreso
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Editorial:
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CRC Press, 2013
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/restrictedAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Matemáticas: Estadística matemática
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Tipo = Sección de libro
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Resumen:
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An important topic in using maps derived from a statistical classifier is the accuracy assessment of the classification. Analysts usually need to compare various techniques, algorithms, or different approaches. As pointed out by Stehman and Czaplewski (1998), the accuracy assessment of classification maps generally involves three different steps: the sampling design, the response or measurement design to obtain the true classes for each sampling (usually requiring an expert), and the analysis of the data obtained. In the ...
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En línea:
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https://eprints.ucm.es/id/eprint/28566/1/Montero243.pdf
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