Rule based Hybrid Weighted Fuzzy Classifier for Tumor Data

Authors

  • D. Winston Paul
  • S. Balakrishnan
  • A. Velusamy

How to Cite

Winston Paul, D., Balakrishnan, S., & Velusamy, A. (2018). Rule based Hybrid Weighted Fuzzy Classifier for Tumor Data. International Journal of Engineering and Technology, 7(4.19), 104-108. https://doi.org/10.14419/ijet.v7i4.19.22030

Received date: November 28, 2018

Accepted date: November 28, 2018

Published date: November 27, 2018

DOI:

https://doi.org/10.14419/ijet.v7i4.19.22030

Keywords:

Data mining, classificaton, Bioinformatics, Fuzzy sytems, genetic algorithms, weighted rule.

Abstract

Examination of gene based information has turned out to be so essential in biomedical industry for assurance of basic ailments. A fuzzy rule based classification is a standout amongst the most mainstream approaches utilized as a part of example arrangement issues. The fuzzy rule based classifier creates an arrangement of fuzzy if-then decides that empower exact non-straight order of information designs. In spite of the fact that there are different techniques to create fluffy if-then guidelines, the advancement of lead producing process is as yet an issue. Here, we introduce a half and half weighted fluffy order framework in which few fluffy if-then principles are chosen by methods for offering weights to preparing designs. Further, we utilize a genetic algorithm (GA) to streamline the classifier for quality articulation investigation

 

 

References

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How to Cite

Winston Paul, D., Balakrishnan, S., & Velusamy, A. (2018). Rule based Hybrid Weighted Fuzzy Classifier for Tumor Data. International Journal of Engineering and Technology, 7(4.19), 104-108. https://doi.org/10.14419/ijet.v7i4.19.22030

Received date: November 28, 2018

Accepted date: November 28, 2018

Published date: November 27, 2018