Machine learning techniques in disease forecasting: a case study on rice blast prediction

BACKGROUND: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction...

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Detalles Bibliográficos
Autores principales: Kaundal, Rakesh, Kapoor, Amar S, Raghava, Gajendra PS
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1647291/
https://www.ncbi.nlm.nih.gov/pubmed/17083731
http://dx.doi.org/10.1186/1471-2105-7-485

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1647291/
https://www.ncbi.nlm.nih.gov/pubmed/17083731
http://dx.doi.org/10.1186/1471-2105-7-485

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