图 书 馆
高维数据的分类：高维判别分析Classification of high dimensional data: High Dimensional Discriminant Analysis |
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| 课程网址: | http://videolectures.net/slsfs05_bouveyron_hdda/ |
| 主讲教师: | Charles Bouveyron |
| 开课单位: | 美国IMAG工业公司 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We propose a new method of discriminant analysis, called High Dimensional Discriminant Analysis (HHDA). Our approach is based on the assumption that high dimensional data live in di erent subspaces with low dimensionality. Thus, HDDA reduces the dimension for each class independently and regularizes class conditional covariance matrices in order to adapt the Gaussian framework to high dimensional data. This regularization is achieved by assuming that classes are spherical in their eigenspace. HDDA is applied to recognize objects in real images and its performances are compared to classical classi cation methods. |
| 关 键 词: | 计算机科学; 机器学习; 监督学习; 操作研究 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-12：yumf |
| 阅读次数: | 91 |