摘要
In this paper, a kernelized version of nonparametric discriminant analysis is proposed that we name KNDA. The main idea is to first map the original data into another high-dimensional space, and then to perform nonparametric discriminant analysis in the high dimensional space. Nonparametric discriminant analysis can relax the Gaussian assumption required for the classical linear discriminant analysis, and Kernel trick can further improve the separation ability. A group of tests on several UCI standard benchmarks have been carried out that prove our proposed method is very promising.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings |
| 页 | 4544-4547 |
| 页数 | 4 |
| DOI | |
| 出版状态 | 已出版 - 2011 |
| 活动 | 2nd Annual Conference on Electrical and Control Engineering, ICECE 2011 - Yichang, 中国 期限: 16 9月 2011 → 18 9月 2011 |
出版系列
| 姓名 | 2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings |
|---|
会议
| 会议 | 2nd Annual Conference on Electrical and Control Engineering, ICECE 2011 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Yichang |
| 时期 | 16/09/11 → 18/09/11 |
指纹
探究 'Kernel nonparametric discriminant analysis' 的科研主题。它们共同构成独一无二的指纹。引用此
Zhan, X., & Ma, B. (2011). Kernel nonparametric discriminant analysis. 在 2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings (页码 4544-4547). 文章 6057678 (2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings). https://doi.org/10.1109/ICECENG.2011.6057678