Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors
Joint Authors
Zhu, William
Zhao, Hong
Min, Fan
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Feature selection is an essential process in data mining applications since it reduces a model’s complexity.
However, feature selection with various types of costs is still a new research topic.
In this paper, we study the cost-sensitive feature selection problem of numeric data with measurement errors.
The major contributions of this paper are fourfold.
First, a new data model is built to address test costs and misclassification costs as well as error boundaries.
It is distinguished from the existing models mainly on the error boundaries.
Second, a covering-based rough set model with normal distribution measurement errors is constructed.
With this model, coverings are constructed from data rather than assigned by users.
Third, a new cost-sensitive feature selection problem is defined on this model.
It is more realistic than the existing feature selection problems.
Fourth, both backtracking and heuristic algorithms are proposed to deal with the new problem.
Experimental results show the efficiency of the pruning techniques for the backtracking algorithm and the effectiveness of the heuristic algorithm.
This study is a step toward realistic applications of the cost-sensitive learning.
American Psychological Association (APA)
Zhao, Hong& Min, Fan& Zhu, William. 2013. Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-496180
Modern Language Association (MLA)
Zhao, Hong…[et al.]. Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors. Journal of Applied Mathematics No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-496180
American Medical Association (AMA)
Zhao, Hong& Min, Fan& Zhu, William. Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-496180
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-496180