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» Predicting Time Series with Support Vector Machines
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ICCS
2007
Springer
14 years 1 months ago
Active Learning with Support Vector Machines for Tornado Prediction
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...
BMCBI
2005
107views more  BMCBI 2005»
13 years 7 months ago
Protein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multip
Background: Predicting the subcellular localization of proteins is important for determining the function of proteins. Previous works focused on predicting protein localization in...
Jiren Wang, Wing-Kin Sung, Arun Krishnan, Kuo-Bin ...
BMCBI
2004
114views more  BMCBI 2004»
13 years 7 months ago
Profiled support vector machines for antisense oligonucleotide efficacy prediction
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
ICANN
2001
Springer
13 years 12 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
BMCBI
2006
106views more  BMCBI 2006»
13 years 7 months ago
Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector
Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their...
H. H. Lin, L. Y. Han, H. L. Zhang, C. J. Zheng, B....