Pattern Discovery in Data Mining

课程
en
英语
16 时
此内容评级为 4.5/5
来源
  • 来自www.coursera.org
状况
  • 自定进度
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更多信息
  • 4 序列
  • 等级 介绍

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课程详情

教学大纲

  • Week 1 - Course Orientation
    The course orientation will get you familiar with the course, your instructor, your classmates, and our learning environment.
  • Week 1 - Module 1
    Module 1 consists of two lessons. Lesson 1 covers the general concepts of pattern discovery. This includes the basic concepts of frequent patterns, closed patterns, max-patterns, and association rules. Lesson 2 covers three major approaches for mining frequent...
  • Week 2 - Module 2
    Module 2 covers two lessons: Lessons 3 and 4. In Lesson 3, we discuss pattern evaluation and learn what kind of interesting measures should be used in pattern analysis. We show that the support-confidence framework is inadequate for pattern evaluation, and ev...
  • Week 3 - Module 3
    Module 3 consists of two lessons: Lessons 5 and 6. In Lesson 5, we discuss mining sequential patterns. We will learn several popular and efficient sequential pattern mining methods, including an Apriori-based sequential pattern mining method, GSP; a vertic...
  • Week 4 - Week 4
    Module 4 consists of two lessons: Lessons 7 and 8. In Lesson 7, we study mining quality phrases from text data as the second kind of pattern mining application. We will mainly introduce two newer methods for phrase mining: ToPMine and SegPhrase, and show fre...

先决条件

没有。

讲师

Jiawei Han
Abel Bliss Professor
Department of Computer Science

编辑

伊利诺伊大学香槟分校(UIUC)成立于 1867 年。伊利诺伊大学的主校区位于芝加哥以南 200 公里处的香槟和厄巴纳双城。

根据世界大学排名中心(Center for World University Rankings)等多项排名,这所重点大学跻身全球最负盛名的大学之列,2020-21 年的全球排名为第 22 位。

平台

Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

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