Majority Voting of Semantic Genetic Programming for Microarray data

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "V. Kanimozhi and B. Chellaprabha",
  booktitle =    "2015 International Conference on Computer
                 Communication and Informatics (ICCCI)",
  title =        "Majority Voting of Semantic Genetic Programming for
                 Microarray data",
  year =         "2015",
  abstract =     "Researchers have found different types of cancer cell
                 along with various normal gene structures in Microarray
                 data. It is possible to set benchmark for finding out
                 affected cell from normal one using various machine
                 learning technique. Due to wide range of gene about
                 thousand of them and minimum training data there occurs
                 imbalance between them. This difference can be
                 minimised using various optimising algorithm and
                 machine learning technique. In this paper we proposed
                 Combined Genetic Programming for Microarray Data along
                 with Majority Voting(MV) for classification. Genetic
                 program along with MV act as both classifier and gene
                 selection. The Quantitative relationships exists among
                 the more frequently selected genes and it has been
                 improved using majority voting techniques. The
                 potential challenge for genetic program is it has to
                 find gene type and also has to find optimal solution
                 from small number of training samples compared to huge
                 number of genes.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICCCI.2015.7218111",
  month =        jan,
  notes =        "CSE, SNS Coll. of Eng., Coimbatore, India

                 Also known as \cite{7218111}",

Genetic Programming entries for V Kanimozhi B Chellaprabha