Classification Based on both Attribute Value Weight and Tuple Weight under the Cloud Computing
Joint Authors
Zheng, Yifeng
Huang, Zaixiang
He, Tianzhong
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-10
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
In recent years, more and more people pay attention to cloud computing.
Users need to deal with magnanimity data in the cloud computing environment.
Classification can predict the need of users from large data in the cloud computing environment.
Some traditional classification methods frequently adopt the following two ways.
One way is to remove instance after it is covered by a rule, another way is to decrease tuple weight of instance after it is covered by a rule.
The quality of these traditional classifiers may be not high.
As a result, they cannot achieve high classification accuracy in some data.
In this paper, we present a new classification approach, called classification based on both attribute value weight and tuple weight (CATW).
CATW is distinguished from some traditional classifiers in two aspects.
First, CATW uses both attribute value weight and tuple weight.
Second, CATW proposes a new measure to select best attribute values and generate high quality classification rule set.
Our experimental results indicate that CATW can achieve higher classification accuracy than some traditional classifiers.
American Psychological Association (APA)
Zheng, Yifeng& Huang, Zaixiang& He, Tianzhong. 2013. Classification Based on both Attribute Value Weight and Tuple Weight under the Cloud Computing. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1009393
Modern Language Association (MLA)
Zheng, Yifeng…[et al.]. Classification Based on both Attribute Value Weight and Tuple Weight under the Cloud Computing. Mathematical Problems in Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1009393
American Medical Association (AMA)
Zheng, Yifeng& Huang, Zaixiang& He, Tianzhong. Classification Based on both Attribute Value Weight and Tuple Weight under the Cloud Computing. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1009393
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009393