图 书 馆
序列分割的递归预测模型Recurrent Predictive Models for Sequence Segmentation |
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| 课程网址: | http://videolectures.net/ida07_mannila_rpm/ |
| 主讲教师: | Heikki Mannila |
| 开课单位: | 赫尔辛基大学 |
| 开课时间: | 2007-10-08 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Many sequential data sets have a segmental structure, and similar types of segments occur repeatedly. We consider sequences where the underlying phenomenon of interest is governed by a small set of models that change over time. Potential examples of such data are environmental, genomic, and economic sequences. Given a target sequence and a (possibly multivariate) sequence of observation values, we consider the problem of finding a small collection of models that can be used to explain the target phenomenon in a piecewise fashion using the observation values. We assume the same model will be used for multiple segments. We give an algorithm for this task based on first segmenting the sequence using dynamic programming, and then using k-median or facility location techniques to find the optimal set of models. We report on some experimental results. |
| 关 键 词: | 计算机科学; 数据集; 动态编程 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-02-10：nkq |
| 阅读次数: | 34 |