Approach to verify new class in the classification process

Author

Teng, Gui-fa ; Li, Ying ; Zhang, Xiao-Ru ; Ma, Jian-Bin ; Chang, Shu-Hui ; Wang, Fang

Author_Institution

Sch. of Inf. Sci. & Technol., Agric. Univ. of Hebei, Baoding, China

Volume

3

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

1743

Abstract

Support vector machine (SVM) is a binary class machine learning classifier. Given a data point, the SVM can classify the data point to either positive class or negative class. However, in some cases, some data points belong to neither positive class nor negative class. They should be treated as one new class. This paper proposes one method that can find isolated data points and separate them into new classes based on F-test and the experimental results show that the method is effective.

Keywords

classification; knowledge verification; learning (artificial intelligence); support vector machines; F-test; binary class; classification; data points; machine learning classifier; new class verification; support vector machine; Cybernetics; Electronic mail; Information science; Machine learning; Risk management; Statistical analysis; Support vector machine classification; Support vector machines; Testing; Training data; F-test; New Class; Support Vector Machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527226

Filename

1527226