[1]LI Huan,WANG Shitong.Binary-class classification algorithm with multiple-access acquired objects based on the SVM[J].CAAI Transactions on Intelligent Systems,2014,9(4):392-400.[doi:10.3969/j.issn.1673-4785.201312040]
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Binary-class classification algorithm with multiple-access acquired objects based on the SVM

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 9 Number of periods: 2014 4 Page number: 392-400 Column: 学术论文—机器学习 Public date: 2014-08-25
Title:
Binary-class classification algorithm with multiple-access acquired objects based on the SVM
Author(s):
LI Huan;  WANG Shitong
1. School of Digital Media, Jiangnan University, Wuxi 214000, China;
2. School of Digital Media, Jiangnan University, Wuxi 214000, China
Keywords:
pattern recognition; multiple observations; similar samples; SVM; binary-class classification
CLC:
TP391.4
DOI:
10.3969/j.issn.1673-4785.201312040
Abstract:
The binary-class classification algorithm with multiple-access acquired objects based on the SVM is proposed for the purpose of classification of an object given with multiple observations in this paper. In each classification, initially all single observation samples in the multiple observation sample set are restricted to a same class.Two hypotheses are made for the class of the multiple observation sample set, and the class is determined by comparing the optimal values of the different objective functions under different class hypotheses. This method does not require training the classifier or early feature representation of the training set, instead, it takes advantage of the continuity law of the feature space of similar samples with the labeled samples and multiple observation samples as a whole, making the algorithm more accurate for classifications. Experiments show that the proposed method is valid and efficient.
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