图 书 馆
一种灵活高效的算法用于正则Fisher判别分析A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_zhang_fearfda/ |
| 主讲教师: | Zhihua Zhang |
| 开课单位: | 浙江大学 |
| 开课时间: | 2010-09-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Fisher linear discriminant analysis (LDA) and its kernel extension—kernel discriminant analysis (KDA)—are well known methods that consider dimensionality reduction and classification jointly. While widely deployed in practical problems, there are still unresolved issues surrounding their efficient implementation and their relationship with least mean squared error procedures. In this paper we address these issues within the framework of regularized estimation. Our approach leads to a flexible and efficient implementation of LDA as well as KDA. We also uncover a general relationship between regularized discriminant analysis and ridge regression. This relationship yields variations on conventional LDA based on the pseudoinverse and a direct equivalence to an ordinary least squares estimator. Experimental results on a collection of benchmark data sets demonstrate the effectiveness of our approach. |
| 关 键 词: | Fisher线性判别分析（LDA）; 机器学习; 内核; 正则化 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-09-28：heyf |
| 阅读次数: | 57 |