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IGARSS
2010
13 years 5 months ago
Support vector machines regression for estimation of forest parameters from airborne laser scanning data
Estimation of forest stand parameters from airborne laser scanning data relies on the selection of laser metrics sets and numerous field plots for model calibration. In mountainou...
Jean-Matthieu Monnet, Frédéric Berge...
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....
BMCBI
2007
139views more  BMCBI 2007»
13 years 7 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
BMCBI
2010
88views more  BMCBI 2010»
13 years 7 months ago
Proteome scanning to predict PDZ domain interactions using support vector machines
Background: PDZ domains mediate protein-protein interactions involved in important biological processes through the recognition of short linear motifs in their target proteins. Tw...
Shirley Hui, Gary D. Bader
ICML
2006
IEEE
14 years 1 months ago
Multiclass reduced-set support vector machines
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...
Benyang Tang, Dominic Mazzoni