图 书 馆
计算生物学中的核方法Kernel Methods in Computational Biology |
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| 课程网址: | http://videolectures.net/mlss06tw_vert_kmcb/ |
| 主讲教师: | Jean-Philippe Vert |
| 开课单位: | 国立巴黎高等矿业学院 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Many problems in computational biology and chemistry can be formalized as classical statistical problems, e.g., pattern recognition, regression or dimension reduction, with the caveat that the data are often not vectors. Indeed objects such as gene sequences, small molecules, protein 3D structures or phylogenetic trees, to name just a few, have particular structures which contain relevant information for the statistical problem but can hardly be encoded into finite-dimensional vector representations. Kernel methods are a class of algorithms well suited for such problems. Indeed they extend the applicability of many statistical methods initially designed for vectors to virtually any type of data, without the need for explicit vectorization of the data. The price to pay for this extension to non-vectors is the need to define a positive definite kernel between the objects, formally equivalent to an implicit vectorization of the data. |
| 关 键 词: | 计算生物学; 统计问题; 内核方法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-10-22：chenxin |
| 阅读次数: | 72 |