Rule based Hybrid Weighted Fuzzy Classifier for Tumor Data

  • Authors

    • D. Winston Paul
    • S. Balakrishnan
    • A. Velusamy
    2018-11-27
    https://doi.org/10.14419/ijet.v7i4.19.22030
  • 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

     

     

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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 & Technology, 7(4.19), 104-108. https://doi.org/10.14419/ijet.v7i4.19.22030

    Received date: 2018-11-28

    Accepted date: 2018-11-28

    Published date: 2018-11-27