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» Variable selection using neural-network models
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CSDA
2007
106views more  CSDA 2007»
14 years 9 months ago
Parsimonious additive models
A new method for function estimation and variable selection, specifically designed for additive models fitted by cubic splines is proposed.This new method involves regularizing ...
Marta Avalos, Yves Grandvalet, Christophe Ambroise
ICIP
2002
IEEE
15 years 2 months ago
Head pose estimation using Gabor eigenspace modeling
In this paper, an approach towards head pose estimation is introduced based on Gabor eigenspace modeling. Gabor filter is used to enhance pose information and eliminate other dist...
Yucheng Wei, Ludovic Fradet, Tieniu Tan
PKDD
2007
Springer
121views Data Mining» more  PKDD 2007»
15 years 3 months ago
Improved Algorithms for Univariate Discretization of Continuous Features
In discretization of a continuous variable its numerical value range is divided into a few intervals that are used in classification. For example, Na¨ıve Bayes can benefit from...
Jussi Kujala, Tapio Elomaa
MICCAI
2008
Springer
15 years 11 months ago
Analysis of Surfaces Using Constrained Regression Models
We present a study of the relationship between the changes in the shape of the human ear due to jaw movement and acoustical feedback (AF) in hearing aids. In particular, we analyze...
Sune Darkner, Mert R. Sabuncu, Polina Golland, ...
WSC
1997
14 years 11 months ago
Sensitivity of Output Performance Measures to Input Distributions in Queueing Simulation Modeling
With modern simulation packages, the modeler can choose almost any standard statistical distribution for generating input random variables. The question arises as to how sensitive...
Donald Gross, Man Juttijudata