图 书 馆
统计声音模式发现Statistically Sound Pattern Discovery |
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| 课程网址: | http://videolectures.net/kdd2014_hamalainen_webb_discovery/ |
| 主讲教师: | Geoff Webb; Wilhelmiina Hämäläinen, School of Computing |
| 开课单位: | 蒙纳士大学 |
| 开课时间: | 2014-10-07 |
| 课程语种: | 英语 |
| 中文简介: |  模式发现是一项核心的数据挖掘活动。最初的方法主要由频繁的模式发现范式主导。仅探索了频繁的模式。经过深入研究，现在已经很好地理解了其局限性，该范式已被两个新兴的替代方法所取代，即信息理论上的最小消息长度范式和统计上合理的范式。本教程涵盖了后者。在此范例中，要求模式通过针对用户定义的零假设的统计检验，从而为寻求的属性提供极大的灵活性，并严格控制错误发现和过度拟合的风险。我们涵盖了这个不断发展的研究领域的理论基础，实际问题，局限性和未来发展方向，并详细探讨了这种模式发现方法如何解决了频繁模式发现范例的许多局限性并可以提供有效的有效发现小套有趣的图案。 |
| 课程简介: | Pattern discovery is a core data mining activity. Initial approaches were dominated by the frequent pattern discovery paradigm | only frequent patterns were explored. Having been thoroughly researched and its limitations now well understood, this paradigm is giving way to two emerging alternatives - the information theoretic minimum message length paradigm and the statistically sound paradigm. This tutorial covers the latter. In this paradigm, patterns are required to pass statistical tests with respect to user defined null-hypotheses, providing great flexibility about the properties that are sought, and strict control over the risk of false discoveries and overfitting. We cover the theoretical foundations, practical issues, limitations and future directions of this growing area of research, as well as explore in detail how this approach to pattern discovery resolves many of the limitations of the frequent pattern discovery paradigm and can deliver efficient and effective discovery of small sets of interesting patterns. |
| 关 键 词: | 模式发现; 统计检验 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-11：zyk |
| 最后编审: | 2020-11-11：zyk |
| 阅读次数: | 35 |