Using the Delta Test for Variable Selection

13 years 5 months ago

Download www.dice.ucl.ac.be

Input selection is an important consideration in all large-scale modelling problems. We propose that using an established noise variance estimator known as the Delta test as the target to minimise can provide an effective input selection methodology. Theoretical justifications and experimental results are presented.

Emil Eirola, Elia Liitiäinen, Amaury Lendasse

Real-time Traffic

ESANN 2008 | Input Selection | Input Selection Methodology | Neural Networks | Noise Variance Estimator |

claim paper

» A multiple testing procedure for input variable selection in neural networks

» Enhancing Automated Test Selection in Probabilistic Networks

» Variable selection using neuralnetwork models

» Estimation of Exercise Energy Expenditure Using a WristWorn Accelerometer A Linear Mixed M...

» DataEfficient InformationTheoretic Test Selection

» Fast Selection of Spectral Variables with BSpline Compression

» VariableSelection Heuristics in Local Search for SAT

» TestTube A System for Selective Regression Testing

Post Info
More Details (n/a)

Added	29 Oct 2010
Updated	29 Oct 2010
Type	Conference
Year	2008
Where	ESANN
Authors	Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen

Comments (0)

Sciweavers

Using the Delta Test for Variable Selection

ESANN 2008 | Input Selection | Input Selection Methodology | Neural Networks | Noise Variance Estimator |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers