The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Multiple Hypothesis Testing for Data Mining
Abstract
A number of important problems in data mining can be usefully addressed within the framework of statistical hypothesis testing. However, while the conventional treatment of statistical significance deals with error probabilities at the level of a single variable, practical data mining tasks tend to involve thousands, if not millions, of variables. This Chapter looks at some of the issues that arise in the application of hypothesis tests to multi-variable data mining problems, and describes two computationally efficient procedures by which these issues can be addressed.
Related Content
Girija Ramdas, Irfan Naufal Umar, Nurullizam Jamiat, Nurul Azni Mhd Alkasirah.
© 2024.
18 pages.
|
Natalia Riapina.
© 2024.
29 pages.
|
Xinyu Chen, Wan Ahmad Jaafar Wan Yahaya.
© 2024.
21 pages.
|
Fatema Ahmed Wali, Zahra Tammam.
© 2024.
24 pages.
|
Su Jiayuan, Zhang Jingru.
© 2024.
26 pages.
|
Pua Shiau Chen.
© 2024.
21 pages.
|
Minh Tung Tran, Thu Trinh Thi, Lan Duong Hoai.
© 2024.
23 pages.
|
|
|