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BMCBI
2006
169views more  BMCBI 2006»
13 years 7 months ago
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 ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
JMLR
2008
116views more  JMLR 2008»
13 years 7 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
CORR
2007
Springer
113views Education» more  CORR 2007»
13 years 7 months ago
Virtual screening with support vector machines and structure kernels
Support vector machines and kernel methods have recently gained considerable attention in chemoinformatics. They offer generally good performance for problems of supervised classi...
Pierre Mahé, Jean-Philippe Vert
ICASSP
2011
IEEE
12 years 11 months ago
Epileptic seizure prediction using the spatiotemporal correlation structure of intracranial EEG
A patient-specific seizure prediction algorithm is proposed that extracts novel multivariate signal coherence features from ECoG recordings and classifies a patient’s pre-seiz...
James R. Williamson, Daniel W. Bliss, David W. Bro...
ECAI
2004
Springer
14 years 1 months ago
A Generalized Quadratic Loss for Support Vector Machines
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Filippo Portera, Alessandro Sperduti