• DocumentCode
    3583283
  • Title

    An algebraic multi-class classification method

  • Author

    He, Qing ; Liu, Zhen-Yan ; Shi, Zhong-zhi

  • Author_Institution
    Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing, China
  • Volume
    5
  • fYear
    2004
  • Firstpage
    3307
  • Abstract
    An algebraic multi-class classification method AHSC, i.e., algebraic hyper surface classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomial in theory, but it is too difficult to separate multi-class data by a single polynomial even though the polynomial is multivalued. AHSC can be used for classifying multi-class data by integrating a series of polynomial networks based on binary numbers, which are used for labeling the classes of samples. The problem that multi-class data cannot always be separated by a single polynomial is solved by AHSC. Moreover, using an adaptive method can choose the order of polynomial. The experimental results show that the new method can efficiently and accurately classify multi-class and high dimension data.
  • Keywords
    learning (artificial intelligence); pattern classification; polynomials; sampling methods; adaptive method; algebraic hyper surface classification; algebraic hyper surface separation; algebraic multiclass data classification method; machine learning; polynomial networks; sampling method; single polynomial theory; Computers; Electronic mail; Error correction codes; Helium; Information processing; Machine learning; Mathematical model; Neurons; Polynomials; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1378609
  • Filename
    1378609