Title :
New Class Recognition Based on Support Vector Data Description
Author :
Xie, Mao-Qiang ; Jiang, Hao ; Huang, Ya-lou ; Sun, Yang
Author_Institution :
Coll. of Software, Nankai Univ., Tianjin
Abstract :
In online classification tasks, such as credit evaluation, spam detection and intrusion detection, new class of patterns sometimes emerges. In order to adapt classifier to the change of distribution, recognition of new class becomes a key problem. To deal with this problem, this paper proposes a novel method based on support vector data description. This method detects and recognizes new class by the description of known classes. The experimental results show that the proposed method can recognize new class well, and on the basis of this technology online classifier is adapted to the change well
Keywords :
learning (artificial intelligence); pattern classification; support vector machines; class recognition; online classification tasks; support vector data description; Cybernetics; Density functional theory; Educational institutions; Electronic mail; Information technology; Intrusion detection; Machine learning; Pattern recognition; Probability density function; Space technology; Sun; Testing; Training data; Adaptive Classification; New Class Recognition; Support Vector Data Description;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258595