The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Instance Selection
|
Author(s): Huan Liu (Arizona State University, USA)and Lei Yu (Arizona State University, USA)
Copyright: 2005
Pages: 4
Source title:
Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch117
PurchaseView Instance Selection on the publisher's website for pricing and purchasing information.
|
Abstract
The amounts of data have become increasingly large in recent years as the capacity of digital data storage worldwide has significantly increased. As the size of data grows, the demand for data reduction increases for effective data mining. Instance selection is one of the effective means to data reduction. This article introduces the basic concepts of instance selection and its context, necessity, and functionality. The article briefly reviews the state-of-the-art methods for instance selection.
Related Content
Md Sakir Ahmed, Abhijit Bora.
© 2024.
15 pages.
|
Lakshmi Haritha Medida, Kumar.
© 2024.
18 pages.
|
Gypsy Nandi, Yadika Prasad.
© 2024.
16 pages.
|
Saurav Bhattacharjee, Sabiha Raiyesha.
© 2024.
14 pages.
|
Naren Kathirvel, Kathirvel Ayyaswamy, B. Santhoshi.
© 2024.
26 pages.
|
K. Sudha, C. Balakrishnan, T. P. Anish, T. Nithya, B. Yamini, R. Siva Subramanian, M. Nalini.
© 2024.
25 pages.
|
Sabiha Raiyesha, Papul Changmai.
© 2024.
28 pages.
|
|
|