Neural Classification and ``Traditional'' Data Analysis: An Application to Households' Living Conditions

Authors:
Sophie Ponthieux;Marie Cottrell
Affiliations:
-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Year:
2001

Citing 3
Cited 0

Self-organization and associative memory: 3rd edition

Self-organization and associative memory: 3rd edition
Self-Organizing Maps

Self-Organizing Maps
The Kohonen Algorithm: A Powerful Tool for Analyzing and Representing Multidimensional Quantitative and Qualitative Data

IWANN '97 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Biological and Artificial Computation: From Neuroscience to Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

The description, classification and 芦 measurement 禄 of living conditions present many difficulties. A very important one comes from the qualitative nature of the data, and the large number of characteristics that may be taken into account. For this reason, it is difficult to obtain a description that could give an overall view of the arrangements between the modalities, and be usable to breakdown the observations into a reasonable number of classes. In this paper, we propose several examples of the use of neural network techniques, precisely the Kohonen algorithm, to classify a population of households according to their characteristics in terms of living conditions.