Genetic Algorithm Based Hybrid Attribute Selection Using Customized Fitness Function

  • C. ArunkumarEmail author
  • S. Ramakrishnan
  • Siva Sai Dheeraj
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)


Attribute selection is an important step in the analysis of gene expression for cancer or illnesses in general. The huge dimensionality of gene expression data that includes many insignificant and redundant genes reduces the classification accuracy. In this study, we propose a hybrid attribute selection method to identify the small set of the most significant genes associated with the cause of cancer. The proposed method integrates the advantages of filter and a wrapper to perform attribute selection by devising a customized fitness function for the genetic algorithm. Three data sets are used that includes leukemia, CNS and colon cancer. Results of our technique are compared with the other standard techniques available in literature. The proposed hybrid approach produces comparably better accuracy than the standard implementation of the genetic algorithm.


Attribute selection Information gain Genetic algorithm Region of characteristic 


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Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  • C. Arunkumar
    • 1
    Email author
  • S. Ramakrishnan
    • 2
  • Siva Sai Dheeraj
    • 1
  1. 1.Department of Computer Science and EngineeringAmrita Vishwa VidyapeethamCoimbatoreIndia
  2. 2.Department of Information TechnologyDr. Mahalingam College of Engineering and TechnologyPollachiIndia

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