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
Link To Document :
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