• DocumentCode
    2256667
  • Title

    Pool-based active learning based on incremental decision tree

  • Author

    Wang, Shuo ; Wang, Jian-jian ; Gao, Xiang-hui ; Wang, Xue-zheng

  • Author_Institution
    Machine Learning Center, Hebei Univ., Baoding, China
  • Volume
    1
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    274
  • Lastpage
    278
  • Abstract
    The pool-based active learning intends to collect the samples into the pool firstly, and selects the best informative sample from it which has no label to add into the training sets for updating the classifier secondly. This paper proposed a new method based on the incremental decision tree algorithm to measure the ambiguity of the unlabeled samples for the sample selection in the active learning.
  • Keywords
    decision trees; learning (artificial intelligence); pattern classification; classifier; incremental decision tree algorithm; pool-based active learning; sample selection; training sets; Accuracy; Algorithm design and analysis; Classification algorithms; Decision trees; Machine learning; Testing; Training; Ambiguity; Incremental decision tree; Pool-based active learning; Sample selection; Unlabeled samples;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5581052
  • Filename
    5581052
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2256667