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TSMC
2010
13 years 2 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
PROMISE
2010
13 years 2 months ago
Modeling the relationship between software effort and size using deming regression
Background: The relation between software effort and size has been modeled in literature as exponential, in the sense that the natural logarithm of effort is expressed as a linear...
Nikolaos Mittas, Makrina Viola Kosti, Vasiliki Arg...
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
INFORMATICALT
2011
112views more  INFORMATICALT 2011»
13 years 2 months ago
The Minimum Density Power Divergence Approach in Building Robust Regression Models
It is well known that in situations involving the study of large datasets where influential observations or outliers maybe present, regression models based on the Maximum Likeliho...
Alessandra Durio, Ennio Davide Isaia
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...