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Home»Articles»An Experimental Analysis on Rough Set Mean, Median, Mode Method of Dependency Values for Feature Selection in Medical Databases

JournalCover

Asian Journal of Computer Science and Technology (AJCST)

Editor Dr. K. Ganesh
Print ISSN : 2249-0701
Frequency : Quarterly

An Experimental Analysis on Rough Set Mean, Median, Mode Method of Dependency Values for Feature Selection in Medical Databases

Author : S. Devi and V. Sasirekha
Volume 8 No.1 Special Issue:February 2019 pp 103-106

Abstract

The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. Recently it became an important issue for scientists, particularly in the area of Artificial Intelligence. Their square measure several approaches to the matter of the way to perceive and manipulate imperfect information. The most successful approach is based on the rough set notion proposed by Z. Pawlak in the article [1]. The proposed method to find the quick reduct in medical data set using the roughest theory. This method has applied in many classification algorithms and find the measures to calculate the accuracy of this proposed method.

Keywords

Rough Set, Dependency Values, Approximation, RST Mean, RST Median, RST Mode

Full Text:

References

[1] Z. Pawlak, “Rough set theory and its applications to data analysis”, Cybernetics and Systems, pp.661-688, 29, Oct. 2010.
[2] C. Wang, M. Shao, Q. He, Y. Qian and Y. Qi, “Feature subset selection based on fuzzy neighborhood rough sets”- Knowledge-based systems, Elsevier, Vol. 111, pp. 173-179, Nov. 2016.
[3] N. Zhong, J. Dong and S. Ohsuga “Using rough sets with heuristics for feature selection”, Journal of intelligent information systems, Springer Vol. 16, No. 3, pp. 199-214, Aug. 2001.
[4] M. Modrzejewski, “Feature selection using rough sets theory”, in Proc. ECML1993, Springer, pp. 216-226, April 1993.
[5] M. S. Raza and U. Qamar, “An incremental dependency calculation technique for feature selection using rough sets”, Information Sciences, Elsevier, Vol. 344, pp. 41-65, May 2016.
[6] Y. Qian, J. Liang, W. Pedrycz and C. Dang ,” Positive approximation: an accelerator for attribute reduction in rough set theory”, Artificial Intelligence, Elsevier, Vol. 174, No. 9-10, pp. 597-618, June 2010
[7] Kuo, Tien-Fang, “Approximate Reducts of an Information System,” in Proc. RSFDGrC 2003, Springer, pp. 291-294, May 2003.
[8] J. Dai and Q. Xu, “Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification”, Applied Soft Computing, Elsevier, Vol. 13, No. 1, Jan2013.
[9] H. H. Inbarani and S. S. Kumar, “Soft rough sets for heart valve disease diagnosis”, in Proc. AMLTA 2014, Springer, pp. 347-356, 2014.
[10] Y. Yao and Y. Zhao, “Attribute reduction in decision-theoretic rough set models”, Information sciences, Elsevier, Vol. 178, No. 17, pp. 3356-3373, Sep. 2008.

Asian Journal of Computer Science and Technology is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and research papers covering all aspects of future computer and Information Technology areas. Topics include, but are not limited to:

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The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. Recently it became an important issue for scientists, particularly in the area of Artificial Intelligence. Their square measure several approaches to the matter of the way to perceive and manipulate imperfect information. The most successful approach is based on the rough set notion proposed by Z. Pawlak in the article [1]. The proposed method to find the quick reduct in medical data set using the roughest theory. This method has applied in many classification algorithms and find the measures to calculate the accuracy of this proposed method.

Editor-in-Chief
Dr. K. Ganesh
Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
Expert at McKinsey and Company, India
[email protected]
Editorial Advisory Board
Dr. Eng. Hamid Ali Abed AL-Asadi
Department of Computer Science, Basra University, Iraq
[email protected]
Dr. Norjihan Binti Abdul Ghani
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Christos Bouras
Department of Computer Engineering & Informatics, University of Patras, Greece
[email protected]
Dr. Maizatul Akmar Binti Ismail
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Harold Castro
Department of Systems Engineering and Computing, University of the Andes, Colombia
[email protected]
Dr. Busyairah Binti Syd Ali
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. Sri Devi Ravana
Department of Information system, University of Malaya, Malaysia
[email protected]
Dr. Karpaga Selvi Subramanian
Department of Computer Engineering, Mekelle University, Ethiopia
[email protected]
Dr. Mazliza Binti Othman
Department of Computer System & Technology, University of Malaya, Malaysia
[email protected]
Dr. Chiam Yin Kia
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. OUH Eng Lieh
Department of Information Systems, Singapore Management University, Singapore
[email protected]

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    Editorial Note

    Editorial Dr. K. Ganesh

    Editor-in-Chief
    Dr. K. Ganesh
    Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
    Expert at McKinsey and Company, India
    [email protected]
    Editorial Advisory Board
    Dr. Eng. Hamid Ali Abed AL-Asadi
    Department of Computer Science, Basra University, Iraq
    [email protected]
    Dr. Norjihan Binti Abdul Ghani
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Christos Bouras
    Department of Computer Engineering & Informatics, University of Patras, Greece
    [email protected]
    Dr. Maizatul Akmar Binti Ismail
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Harold Castro
    Department of Systems Engineering and Computing, University of the Andes, Colombia
    [email protected]
    Dr. Busyairah Binti Syd Ali
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. Sri Devi Ravana
    Department of Information system, University of Malaya, Malaysia
    [email protected]
    Dr. Karpaga Selvi Subramanian
    Department of Computer Engineering, Mekelle University, Ethiopia
    [email protected]
    Dr. Mazliza Binti Othman
    Department of Computer System & Technology, University of Malaya, Malaysia
    [email protected]
    Dr. Chiam Yin Kia
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. OUH Eng Lieh
    Department of Information Systems, Singapore Management University, Singapore
    [email protected]

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