most citedMutual information for the selection of relevant variables in spectrometric nonlinear modelling

219 citations · 557 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NE200834 cited

A data-driven functional projection approach for the selection of feature ranges in spectra with ICA or cluster analysis

Catherine Krier, Fabrice Rossi, Damien François +1

Prediction problems from spectra are largely encountered in chemometry. In addition to accurate predictions, it is often needed to extract information about which wavelengths in th…

cs.NE2007126 cited

Representation of Functional Data in Neural Networks

Fabrice Rossi, Nicolas Delannay, Brieuc Conan-Guez +1

Functional Data Analysis (FDA) is an extension of traditional data analysis to functional data, for example spectra, temporal series, spatio-temporal images, gesture recognition da…

cs.LG2007131 cited

Resampling methods for parameter-free and robust feature selection with mutual information

Damien François, Fabrice Rossi, Vincent Wertz +1

Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time.…

cs.LG200747 cited

Fast Selection of Spectral Variables with B-Spline Compression

Fabrice Rossi, Damien François, Vincent Wertz +2

The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables h…

cs.LG2007219 cited

Mutual information for the selection of relevant variables in spectrometric nonlinear modelling

Fabrice Rossi, Amaury Lendasse, Damien François +2

Data from spectrophotometers form vectors of a large number of exploitable variables. Building quantitative models using these variables most often requires using a smaller set of…