|
| << previous | next >> |
Journal description
All volumes of the corresponding journal
All issues of the corresponding volume
All articles of the corresponding issues
Details for article 7 of 14 found articles
| Title: |
Identification of Influential Cases in Kernel Fisher Discriminant Analysis |
| Author: |
Louw, Nelmarie Lamont, Morne M. C. Steel, Sarel J. |
| Appeared in: |
Communications in statistics |
| Paging: | Volume 37 (2008) nr. 10 pages 2050-2062 |
| Year: |
2008-11 |
| Contents: |
We study the influence of a single data case on the results of a statistical analysis. This problem has been addressed in several articles for linear discriminant analysis (LDA). Kernel Fisher discriminant analysis (KFDA) is a kernel based extension of LDA. In this article, we study the effect of atypical data points on KFDA and develop criteria for identification of cases having a detrimental effect on the classification performance of the KFDA classifier. We find that the criteria are successful in identifying cases whose omission from the training data prior to obtaining the KFDA classifier results in reduced error rates. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 7 of 14 found articles
| << previous | next >> |