title: Machine learning techniques in disease forecasting: a case study on rice blast prediction.
creator: Kaundal, Rakesh
creator: Kapoor, Amar S
creator: Raghava, G.P.S.
subject: QR Microbiology
description: Our case study demonstrated that SVM is better than existing machine learning techniques and conventional REG approaches in forecasting plant diseases. In this direction, we have also developed a SVM-based web server for rice blast prediction, a first of its kind worldwide, which can help the plant science community and farmers in their decision making process. The server is freely available at http://www.imtech.res.in/raghava/rbpred/.
publisher: Biomedcentral
date: 2006
type: Article
type: PeerReviewed
format: application/pdf
identifier: http://crdd.osdd.net/open/131/1/raghava2006.pdf
relation: http://www.biomedcentral.com/1471-2105/7/485
identifier:   Kaundal, Rakesh and Kapoor, Amar S and Raghava, G.P.S.  (2006) Machine learning techniques in disease forecasting: a case study on rice blast prediction.  BMC bioinformatics, 7.  p. 485.  ISSN 1471-2105     
relation: http://crdd.osdd.net/open/131/