Supervised variable clustering for classification of NIR spectra

ESANN 2009 Proceedings, 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning

Volumn , Issue , 2009, Pages 263-268

  Krier, Catherine ^a   François, Damien ^a   Rossi, Fabrice ^b   Verleysen, Michel ^a  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^b INSTITUT TELECOM   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS;

BETTER PERFORMANCE; DIMENSION REDUCTION; HIGH-DIMENSIONAL; NIR SPECTRUM; SPECTRAL RANGE; SPECTRAL VARIABLES; SPECTROMETRIC DATA; TWO SOURCES;

NEURAL NETWORKS;

EID: 84886996104     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. C. Krier, F. Rossi, D. François, M. Verleysen: A data-driven functional projection approach for the selection of feature ranges in spectra with ICA or cluster analysis; Chemometrics and Intelligent Laboratory Systems, vol. 91, pp. 43-53, Elsevier (2008).
2. G. Van Dijk, M. Van Hulle: Speeding Up the Wrapper Feature Subset Selection in Regression by Mutual Information Relevance and Redundancy Analysis, proceedings of the International Conference of Artificial Neural Network, pp. 3140, Springer, Heidelberg (2006).
3. D. François, C. Krier, F. Rossi, M. Verleysen: Estimation de redondance pour le clustering de variables spectrales, proceedings of the AGROSTAT 2008 10th European Symposium on Statistical Methods for the Food Industry, pp. 5561, Louvain-la-Neuve/Belgium (2008).
4. I. Guyon, S. Gunn, M. Nikravesh, L. A. Zadeh, Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing), Springer (2006).
5. V. Gomez-Verdejo, M. Verleysen, J. Fleury, Information-theoretic feature selection for the classification of hysteresis curves, proceedings of the IWANN'07, International Work-Conference on Artificial Neural Networks, San Sebastian (Spain). Computational and Ambiant Intelligence, Francisco Sandoval et al. eds., Springer (Berlin-Heidelberg), Lecture Notes in Computer Science 4507, pp. 522-529 (2007).
6. Tecator meat sample dataset, http://lib.stat.cmu.edu/datasets/tecator.
7. Dataset provided by Prof. Marc Meurens, Université catholique de Louvain, BNUT unit, meurens@bnut.ucl.ac.be. Available from http://www.ucl.ac.be/mlg/index.php?page=DataBases.
8. F. Rossi, A. Lendassse, D. François, V. Wertz, M. Verleysen: Mutual information for the selection of relevant variables in spectrometric nonlinear modeling, Chemometrics and Intelligent Laboratory Systems, vol. 80, pp. 215226, Elsevier (2006).