• DocumentCode
    259529
  • Title

    Fast Numerical Threshold Search Algorithm for C4.5

  • Author

    Wen-Mau Chong ; Chien-Le Goh ; Yoon-Teck Bau ; Kian-Chin Lee

  • Author_Institution
    Fac. of Comput. & Inf., Multimedia Univ., Cyberjaya, Malaysia
  • fYear
    2014
  • fDate
    Aug. 31 2014-Sept. 4 2014
  • Firstpage
    930
  • Lastpage
    935
  • Abstract
    This paper presents a new algorithm to improve the speed of threshold searching process in C4.5 by using the technique of genetic algorithms. In the threshold searching process in C4.5, the values in a numerical attribute are sorted first and then the mid-point between every two consecutive values is calculated and designated as a candidate threshold. This process can be time consuming and it is not practical for large data. Our algorithm generates a population of possible thresholds and converges to the best threshold value rapidly. Our experimental results have shown that significant time reduction has been achieved by using our algorithm in threshold searching process.
  • Keywords
    data mining; decision trees; genetic algorithms; learning (artificial intelligence); pattern classification; C4.5 algorithm; decision tree algorithm; genetic algorithms; large data; machine learning; threshold searching process; Accuracy; Biological cells; Decision trees; Genetic algorithms; Sociology; Statistics; Training; classification; decision tree algorithm; genetic algorithm; numerical attribute;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Applied Informatics (IIAIAAI), 2014 IIAI 3rd International Conference on
  • Conference_Location
    Kitakyushu
  • Print_ISBN
    978-1-4799-4174-2
  • Type

    conf

  • DOI
    10.1109/IIAI-AAI.2014.183
  • Filename
    6913427