• DocumentCode
    2036538
  • Title

    An E-SMOTE technique for feature selection in High-Dimensional Imbalanced Dataset

  • Author

    Deepa, T. ; Punithavalli, M.

  • Author_Institution
    Comput. Sci., Karpagam Univ., Coimbatore, India
  • Volume
    2
  • fYear
    2011
  • fDate
    8-10 April 2011
  • Firstpage
    322
  • Lastpage
    324
  • Abstract
    Feature Selection in High-Dimensional Imbalanced Dataset (where one class outnumbers the other class) plays an imperative task in field of Data mining and Bio-informatics. This paper proposes a new technique called E-SMOTE Technique for balancing the dataset and SVM classification for selecting the features. It is evaluated using micro array dataset.
  • Keywords
    bioinformatics; data mining; pattern classification; support vector machines; E-SMOTE technique; SVM classification; bio-informatics; data mining; dataset balancing; feature selection; high-dimensional imbalanced dataset; micro array dataset; Bioinformatics; Cancer; Data mining; Feature extraction; Genetic algorithms; Machine learning; Support vector machines; E-SMOTE; Featue Selection; Imbalanced dataset; Support Vector Machine[SVM];
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics Computer Technology (ICECT), 2011 3rd International Conference on
  • Conference_Location
    Kanyakumari
  • Print_ISBN
    978-1-4244-8678-6
  • Electronic_ISBN
    978-1-4244-8679-3
  • Type

    conf

  • DOI
    10.1109/ICECTECH.2011.5941710
  • Filename
    5941710
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2036538