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RETRACTED ARTICLE: Tolerance rough set firefly-based quick reduct

Neural Computing and Applications volume 28, pages 2995–3008 (2017)Cite this article

This article was retracted on 02 January 2023

This article has been updated

Abstract

In medical information system, there are a lot of features and the relationship among elements is solid. In this way, feature selection of medical datasets gets awesome worry as of late. In this article, tolerance rough set firefly-based quick reduct, is developed and connected to issue of differential finding of diseases. The hybrid intelligent framework intends to exploit the advantages of the fundamental models and, in the meantime, direct their restrictions. Feature selection is procedure for distinguishing ideal feature subset of the original features. A definitive point of feature selection is to build the precision, computational proficiency and adaptability of expectation strategy in machine learning, design acknowledgment and information mining applications. Along these lines, the learning framework gets a brief structure without lessening the prescient precision by utilizing just the chose remarkable features. In this research, a hybridization of two procedures, tolerance rough set and as of late created meta-heuristic enhancement calculation, the firefly algorithm is utilized to choose the conspicuous features of medicinal information to have the capacity to characterize and analyze real sicknesses. The exploratory results exhibited that the proficiency of the proposed system outflanks the current supervised feature selection techniques.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Sona College of Technology (Autonomous), Salem, Tamil Nadu, 636 005, India

    Jothi Ganesan

  2. Department of Computer Science, Periyar University, Salem, Tamil Nadu, 636 011, India

    Hannah H. Inbarani

  3. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

  4. Department of Electrical and Electronics Engineering, Faculty of Engineering and Architecture, Abant Izzet Baysal University, 14280, Bolu, Turkey

    Kemal Polat

Authors
  1. Jothi Ganesan
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  2. Hannah H. Inbarani
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  3. Ahmad Taher Azar
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  4. Kemal Polat
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Corresponding author

Correspondence to Ahmad Taher Azar.

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All authors declare that they have no conflict of interest.

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Cite this article

Ganesan, J., Inbarani, H.H., Azar, A.T. et al. RETRACTED ARTICLE: Tolerance rough set firefly-based quick reduct. Neural Comput & Applic 28, 2995–3008 (2017). https://doi.org/10.1007/s00521-016-2514-2

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  • DOI: https://doi.org/10.1007/s00521-016-2514-2

Keywords

  • Rough set theory
  • Tolerance rough set
  • Firefly algorithm
  • Soft computing techniques
  • Swarm intelligent
  • Supervised feature selection