Decision Making Using Rough Topology and Indiscernibility Matrix for Diagnosing Disease

Authors

  • Kaarthiga S  M.Sc., Mathematics, Department of Mathematics, Dr. SNS Rajalakshmi College of Arts and Science (Autonomous), Coimbatore, Tamilnadu, India
  • K. Sangeetha  Assistant Professor, Department of Mathematics, Dr. SNS Rajalakshmi College of Arts and Science (Autonomous), Coimbatore, Tamilnadu, India

DOI:

https://doi.org/10.32628/18410IJSRSET

Keywords:

Rough Sets, Set Approximation, Equivalence Class, Basis, Indiscernibility Matrix.

Abstract

Rough set theory has provided the necessary formalism and ideas for the development of some propositional machine learning systems. An important feature of rough sets is that the theory is followed by practical implementations of toolkits that support interactive model development. The main objective of this paper is to introduce and analyze the Rough Set Theory and also to decide the factors for diseases by using Indiscernibility and Boolean law.

References

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  2. 2Nirmala Rebeccca Paul, "Rough Topology Based Decision Making in Medical Diagnosis", International Journal of Mathematics Trends and Technology – Volume 18 Number 1 – Feb 2015
  3. 3Silvia Rissino and Germano Lambert-Torres, "Rough Set Theory – Fundamental Concepts, Principals, Data Extraction, and Applications".
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  6. Salama,A.S., "Some topological properties of rough sets with tools for data mining", IJCSI International Journal of Computer Science issues 8 (2011) 588-595

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-09-30

Issue

Volume 4, Issue 10, September-October-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Kaarthiga S, K. Sangeetha "Decision Making Using Rough Topology and Indiscernibility Matrix for Diagnosing Disease" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 10, pp.135-138, September-October-2018. Available at doi : https://doi.org/10.32628/18410IJSRSET