Abstract
Both Linear Discriminant Analysis and Support Vector Machines compute hyperplanes that are optimal with respect to their individual objectives. However, there can be vast differences in performance between the two techniques depending on the extent to which their respective assumptions agree with problems at hand. In this paper we compare the two techniques analytically and experimentally using a number of data sets. For analytical comparison purposes, a unified representation is developed and a metric of optimality is proposed.
| Original language | English |
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| Title of host publication | Advances in Information Systems - Second International Conference, ADVIS 2002 Izmir, Turkey, October 23-25, 2002 Proceedings |
| Editors | Tatyana Yakhno |
| Publisher | Springer Verlag |
| Pages | 104-113 |
| Number of pages | 10 |
| ISBN (Print) | 3540000097, 9783540000099 |
| Publication status | Published - 1 Jan 2002 |
| Event | 2nd International Conference on Advances in Information Systems, ADVIS 2002 - Izmir, Turkey Duration: 23 Oct 2002 → 25 Oct 2002 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 2457 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 2nd International Conference on Advances in Information Systems, ADVIS 2002 |
|---|---|
| Country | Turkey |
| City | Izmir |
| Period | 23/10/02 → 25/10/02 |
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Cite this
Gokcen, I., & Peng, J. (2002). Comparing linear discriminant analysis and support vector machines. In T. Yakhno (Ed.), Advances in Information Systems - Second International Conference, ADVIS 2002 Izmir, Turkey, October 23-25, 2002 Proceedings (pp. 104-113). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2457). Springer Verlag.