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Comparative analysis of the EFuNN and the Support Vector Machine models for the classification of horticulture data

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Comparative analysis of the EFuNN and the Support Vector Machine models for the classification of horticulture data
Id. 46207052
Idioma inglés
Titulo Comparative analysis of the EFuNN and the Support Vector Machine models for the classification of horticulture data
Autor(es) Brendon J. Woodford
Localización http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.4285
Versión 1.0
Estado Final
Descripción Support Vector Machines (SVM) over the past six years have emerged as one of the more robust classification architectures coupled with good generalisation capabilities. Similarly the Evolving Fuzzy Neural Network (EFuNN) have also been reported to posses these properties as well. This paper compares these two models and then applies them to the classification of two datasets taken from the horticulture industry. The results that are reported indicate that the EFuNN performs comparably well against its statistically based counterpart.
Tipo application/pdf
Tipo de recurso Texto Narrativo
Tipo de Interactividad Expositivo
Nivel de Interactividad muy bajo
Audiencia Estudiante
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Estructura Atomic
Coste no
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Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Formatos application/pdf
Requerimientos técnicos Browser: Any
Relación [IsBasedOn] http://divcom.otago.ac.nz/infosci/kel/CBIIS/pubs/pdf/wood-kasa-annes2001.pdf
[References] 10.1.1.15.9362
[References] 10.1.1.102.7476
[References] 10.1.1.34.4986
[References] 10.1.1.21.1720
[References] 10.1.1.83.6711
[References] 10.1.1.19.8015
[References] 10.1.1.108.12
[References] 10.1.1.4.1097
Fecha de contribución 22-jul-2009
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