Input Selection and Regression using the Som
Abstract
This Paper Presents a Global Methodology to Build a Nonlinear Regression When the Number of Available Samples is Small Compared to the Number of Inputs. the Task is Divided in Two Parts: Selection of the Best Inputs and Construction of the Approximator. a First Som is Used to Compute Clean Correlations between the Inputs and the Output. a Second Som is Built to Link the Output to the Selected Inputs. the Good Performances of This Methodology Are Illustrated on a Spectrometric Dataset.
Recommended Citation
F. Corona and A. Lendasse, "Input Selection and Regression using the Som," WSOM 2005 - 5th Workshop on Self-Organizing Maps, pp. 653 - 660, WSOM, Dec 2005.
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Regression; Self-organizing maps; Spectrometry; Variable selection
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 WSOM, All rights reserved.
Publication Date
01 Dec 2005