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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. 41962715
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://citeseer.ist.psu.edu/527170.html
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 pdf
Palabras clave Brendon J. Woodford Comparative analysis of the EFuNN and the Support Vector Machine models for the classification of horticulture data
Tipo de Interactividad Expositivo
Nivel de Interactividad muy bajo
Audiencia Estudiante
Profesor
Autor
Estructura Atomic
Coste no
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unrestricted
Formatos pdf
Requerimientos técnicos Browser: Any
Relación [IsBasedOn] http://divcom.otago.ac.nz/infosci/kel/CBIIS/pubs/pdf/wood-kasa-annes2001.pdf
[References] oai:CiteSeerPSU:454996
[References] oai:CiteSeerPSU:500489
[References] oai:CiteSeerPSU:541088
[References] oai:CiteSeerPSU:304819
[References] oai:CiteSeerPSU:543919
Fecha de contribución 31-mar-2009
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