Label Propagation Algorithm Based on Over-Relaxation Iteration
GE Fang1, GUO Youqiang1, WANG Nian2
1.Department of Computer Science and Technology, Bengbu University, Bengbu 233030 2.Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education,Anhui University, Hefei 230039
Abstract Aiming at the problem in the label propagation algorithm, over-relaxation iteration is introduced to solve the optimization problem of label sequence and an improved label propagation algorithm based on over-relaxation iteration (ORLP) is presented. The known samples are labeled with positive and negative labels and the label information of unknown samples is predicted by learning the classification between neighbor points. Meanwhile, the label information of initial labeled samples is reserved in each iteration to guide the next label propagation process. In addition, grounded on over-relaxation iteration, the label propagation formula of ORLP is inferred and the convergence of label sequence is proved simultaneously. Thus, the convergence solution of label sequence is obtained. The experimental results show that the ORLP has higher classification accuracy and convergence speed.
Fund:Supported by National Natural Science Foundation of China(No.41001292), Natural Science Foundation of Anhui Province (No.11040606M151), Natural Science Foundation of Bengbu University (No.2014ZR26)
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2016, Vol. 29 
