Soft Computing

, Volume 23, Issue 23, pp 12655–12672 | Cite as

A hybrid approach using rough set theory and hypergraph for feature selection on high-dimensional medical datasets

  • M. R. Gauthama Raman
  • Somu Nivethitha
  • Krithivasan Kannan
  • V. S. Shankar SriramEmail author
Methodologies and Application


‘Curse of Dimensionality’—massive generation of high-dimensional medical datasets from various biomedical applications hardens the data analytic process for precise medical diagnosis. The design of an efficient feature selection technique for finding the optimal feature subset can be devised as a prominent solution to the above-said challenge. Further, it also improves the accuracy and minimizes the computational complexity of the learning model. The state-of-the-art feature selection techniques based on heuristic and statistical functions suffer from significant challenges in terms of classification accuracy, time complexity, etc. Hence, this paper presents Rough Set Theory and Hypergraph (RSHGT)-based feature selection technique to identify the optimal feature subset for accurate medical diagnosis. Experimental validations using six medical datasets from the Kent Ridge Biomedical dataset repository prove the efficiency of RSHGT in terms of reduct size, accuracy, precision, recall, and time complexity.


Hypergraph Rough set theory (RST) Vertex linearity Minimal transversal Medical diagnosis 



This work was supported by The Department of Science and Technology – India, and TATA Realty – SASTRA Srinivasa Ramanujan Research Cell (Grant No: SR/FST/MSI-107/2015, MRT/2017/000155, and SR/FST/ETI-349/2013).

Compliance with ethical standards

Conflict of interest

All the authors declare that they do not have any conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Centre for Information Super Highway (CISH), School of ComputingSASTRA Deemed to be UniversityThanjavurIndia
  2. 2.Data Science Laboratory, Department of MathematicsSASTRA Deemed to be UniversityThanjavurIndia
  3. 3.iTrust, Centre for Research in Cyber SecuritySingapore University of Technology and DesignSingaporeSingapore
  4. 4.Smart Energy Informatics Lab (SEIL), Department of Computer Science and EngineeringIndian Institute of Technology-BombayMumbaiIndia

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