On the effects of dimensionality on data analysis with neural networks

Verleysen, Michel;François, Damien;Simon, Geoffroy;Wertz, Vincent
(2003) 7th International Work Conference on Artificial and Natural Neural Networks (IWANN 2003) — Location: Menorca (Spain) (3.June.2003)

Files

pdfdocument.pdf
  • Restricted Access
  • Adobe PDF
  • 150.81 KB
Request a copy

Details

Authors
Abstract
Modem data analysis often faces high-dimensional data. Nevertheless, most neural network data analysis tools are not adapted to high-dimensional spaces, because of the use of conventional concepts (as the Euclidean distance) that scale poorly with dimension. This paper shows some limitations of such concepts and suggests some research directions as the use of alternative distance definitions and of non-linear dimension reduction.
Affiliations

Citations

  • APA
  • Chicago
  • FWB

Verleysen, M., François, D., Simon, G., & Wertz, V. (2003). On the effects of dimensionality on data analysis with neural networks. Lecture Notes in Computer Science, 2687, 105-112. https://doi.org/10.1007/3-540-44869-1_14 (Original work published 2003)