• DocumentCode
    2363699
  • Title

    INNE: a structured learning algorithm for noisy examples

  • Author

    Liquiere, Michel ; Sallantin, Jean

  • Author_Institution
    CRIM, Montpellier, France
  • fYear
    1989
  • fDate
    23-25 Oct 1989
  • Firstpage
    70
  • Lastpage
    76
  • Abstract
    A technique for learning structural concepts from noisy examples is presented. Using the description language defined by J.F. Sowa (1984) provides a convenient way of expressing the knowledge and the properties used by the algorithm. This graph description makes it possible to better manage learning problems, define new methods, and present results in a familiar and practical way. A learning system INNE has been developed which is based on this kind of description language. The goal is to design a learning algorithm which allows the processing of a considerable amount of data in a reasonable time. This kind of learning engine has been successfully tested on a real problem in biology. Thus, an experimental basis and a validation of the method have been acquired
  • Keywords
    knowledge acquisition; knowledge based systems; learning systems; INNE; biology; description language; graph description; knowledge acquisition; learning engine; learning problems; noisy examples; structured learning algorithm; Algorithm design and analysis; Diseases; Learning systems; Logic; Machine learning; Machine learning algorithms; Mechanical factors; Medical treatment; Testing; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools for Artificial Intelligence, 1989. Architectures, Languages and Algorithms, IEEE International Workshop on
  • Conference_Location
    Fairfax, VA
  • Print_ISBN
    0-8186-1984-8
  • Type

    conf

  • DOI
    10.1109/TAI.1989.65304
  • Filename
    65304